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authorN.N. <sevyves@users.sourceforge.net>2009-08-15 12:57:31 +0000
committerN.N. <sevyves@users.sourceforge.net>2009-08-15 12:57:31 +0000
commit7cabbe3dcaa0ef520f0caaf4009bd9add5474011 (patch)
treecdd14992168f67d7888a30a37ef51f03ccb20a7d /haarcascades
parent9952f0e57d7d6b18e8a83257ec89746365c5a0cd (diff)
added threshold
svn path=/trunk/externals/pix_opencv/; revision=11922
Diffstat (limited to 'haarcascades')
-rwxr-xr-xhaarcascades/haarcascade_frontalface_alt.xml26161
-rw-r--r--haarcascades/haarcascade_frontalface_alt2.xml23550
-rw-r--r--haarcascades/haarcascade_frontalface_alt_tree.xml103493
-rw-r--r--haarcascades/haarcascade_frontalface_default.xml35712
-rw-r--r--haarcascades/haarcascade_fullbody.xml18118
-rw-r--r--haarcascades/haarcascade_lowerbody.xml15085
-rw-r--r--haarcascades/haarcascade_profileface.xml31930
-rw-r--r--haarcascades/haarcascade_upperbody.xml29767
-rwxr-xr-xhaarcascades/mouth.xml21991
9 files changed, 305807 insertions, 0 deletions
diff --git a/haarcascades/haarcascade_frontalface_alt.xml b/haarcascades/haarcascade_frontalface_alt.xml
new file mode 100755
index 0000000..af48bab
--- /dev/null
+++ b/haarcascades/haarcascade_frontalface_alt.xml
@@ -0,0 +1,26161 @@
+<?xml version="1.0"?>
+<!--
+ Stump-based 20x20 gentle adaboost frontal face detector.
+ Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+ IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+ By downloading, copying, installing or using the software you agree to this license.
+ If you do not agree to this license, do not download, install,
+ copy or use the software.
+
+
+ Intel License Agreement
+ For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistribution's of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistribution's in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * The name of Intel Corporation may not be used to endorse or promote products
+ derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<haarcascade_frontalface_alt type_id="opencv-haar-classifier">
+ <size>20 20</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>3 7 14 4 -1.</_>
+ <_>3 9 14 2 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>4.0141958743333817e-003</threshold>
+ <left_val>0.0337941907346249</left_val>
+ <right_val>0.8378106951713562</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>1 2 18 4 -1.</_>
+ <_>7 2 6 4 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>0.0151513395830989</threshold>
+ <left_val>0.1514132022857666</left_val>
+ <right_val>0.7488812208175659</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>1 7 15 9 -1.</_>
+ <_>1 10 15 3 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>4.2109931819140911e-003</threshold>
+ <left_val>0.0900492817163467</left_val>
+ <right_val>0.6374819874763489</right_val></_></_></trees>
+ <stage_threshold>0.8226894140243530</stage_threshold>
+ <parent>-1</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 1 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 6 2 6 -1.</_>
+ <_>5 9 2 3 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>1.6227109590545297e-003</threshold>
+ <left_val>0.0693085864186287</left_val>
+ <right_val>0.7110946178436279</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>7 5 6 3 -1.</_>
+ <_>9 5 2 3 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>2.2906649392098188e-003</threshold>
+ <left_val>0.1795803010463715</left_val>
+ <right_val>0.6668692231178284</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>4 0 12 9 -1.</_>
+ <_>4 3 12 3 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>5.0025708042085171e-003</threshold>
+ <left_val>0.1693672984838486</left_val>
+ <right_val>0.6554006934165955</right_val></_></_>
+ <_>
+ <!-- tree 3 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>6 9 10 8 -1.</_>
+ <_>6 13 10 4 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>7.9659894108772278e-003</threshold>
+ <left_val>0.5866332054138184</left_val>
+ <right_val>0.0914145186543465</right_val></_></_>
+ <_>
+ <!-- tree 4 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>3 6 14 8 -1.</_>
+ <_>3 10 14 4 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-3.5227010957896709e-003</threshold>
+ <left_val>0.1413166970014572</left_val>
+ <right_val>0.6031895875930786</right_val></_></_>
+ <_>
+ <!-- tree 5 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>14 1 6 10 -1.</_>
+ <_>14 1 3 10 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>0.0366676896810532</threshold>
+ <left_val>0.3675672113895416</left_val>
+ <right_val>0.7920318245887756</right_val></_></_>
+ <_>
+ <!-- tree 6 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>7 8 5 12 -1.</_>
+ <_>7 12 5 4 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>9.3361474573612213e-003</threshold>
+ <left_val>0.6161385774612427</left_val>
+ <right_val>0.2088509947061539</right_val></_></_>
+ <_>
+ <!-- tree 7 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>1 1 18 3 -1.</_>
+ <_>7 1 6 3 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>8.6961314082145691e-003</threshold>
+ <left_val>0.2836230993270874</left_val>
+ <right_val>0.6360273957252502</right_val></_></_>
+ <_>
+ <!-- tree 8 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>1 8 17 2 -1.</_>
+ <_>1 9 17 1 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>1.1488880263641477e-003</threshold>
+ <left_val>0.2223580926656723</left_val>
+ <right_val>0.5800700783729553</right_val></_></_>
+ <_>
+ <!-- tree 9 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>16 6 4 2 -1.</_>
+ <_>16 7 4 1 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-2.1484689787030220e-003</threshold>
+ <left_val>0.2406464070081711</left_val>
+ <right_val>0.5787054896354675</right_val></_></_>
+ <_>
+ <!-- tree 10 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 17 2 2 -1.</_>
+ <_>5 18 2 1 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>2.1219060290604830e-003</threshold>
+ <left_val>0.5559654831886292</left_val>
+ <right_val>0.1362237036228180</right_val></_></_>
+ <_>
+ <!-- tree 11 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>14 2 6 12 -1.</_>
+ <_>14 2 3 12 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-0.0939491465687752</threshold>
+ <left_val>0.8502737283706665</left_val>
+ <right_val>0.4717740118503571</right_val></_></_>
+ <_>
+ <!-- tree 12 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>4 0 4 12 -1.</_>
+ <_>4 0 2 6 2.</_>
+ <_>6 6 2 6 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>1.3777789426967502e-003</threshold>
+ <left_val>0.5993673801422119</left_val>
+ <right_val>0.2834529876708984</right_val></_></_>
+ <_>
+ <!-- tree 13 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>2 11 18 8 -1.</_>
+ <_>8 11 6 8 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>0.0730631574988365</threshold>
+ <left_val>0.4341886043548584</left_val>
+ <right_val>0.7060034275054932</right_val></_></_>
+ <_>
+ <!-- tree 14 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 7 10 2 -1.</_>
+ <_>5 8 10 1 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>3.6767389974556863e-004</threshold>
+ <left_val>0.3027887940406799</left_val>
+ <right_val>0.6051574945449829</right_val></_></_>
+ <_>
+ <!-- tree 15 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>15 11 5 3 -1.</_>
+ <_>15 12 5 1 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-6.0479710809886456e-003</threshold>
+ <left_val>0.1798433959484100</left_val>
+ <right_val>0.5675256848335266</right_val></_></_></trees>
+ <stage_threshold>6.9566087722778320</stage_threshold>
+ <parent>0</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 2 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 3 10 9 -1.</_>
+ <_>5 6 10 3 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-0.0165106896311045</threshold>
+ <left_val>0.6644225120544434</left_val>
+ <right_val>0.1424857974052429</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>9 4 2 14 -1.</_>
+ <_>9 11 2 7 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>2.7052499353885651e-003</threshold>
+ <left_val>0.6325352191925049</left_val>
+ <right_val>0.1288477033376694</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>3 5 4 12 -1.</_>
+ <_>3 9 4 4 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>2.8069869149476290e-003</threshold>
+ <left_val>0.1240288019180298</left_val>
+ <right_val>0.6193193197250366</right_val></_></_>
+ <_>
+ <!-- tree 3 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>4 5 12 5 -1.</_>
+ <_>8 5 4 5 3.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-1.5402400167658925e-003</threshold>
+ <left_val>0.1432143002748489</left_val>
+ <right_val>0.5670015811920166</right_val></_></_>
+ <_>
+ <!-- tree 4 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 6 10 8 -1.</_>
+ <_>5 10 10 4 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-5.6386279175058007e-004</threshold>
+ <left_val>0.1657433062791824</left_val>
+ <right_val>0.5905207991600037</right_val></_></_>
+ <_>
+ <!-- tree 5 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>8 0 6 9 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>1.9253729842603207e-003</threshold>
+ <left_val>0.2695507109165192</left_val>
+ <right_val>0.5738824009895325</right_val></_></_>
+ <_>
+ <!-- tree 6 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>9 12 1 8 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-5.0214841030538082e-003</threshold>
+ <left_val>0.1893538981676102</left_val>
+ <right_val>0.5782774090766907</right_val></_></_>
+ <_>
+ <!-- tree 7 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>0 7 20 6 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>2.6365420781075954e-003</threshold>
+ <left_val>0.2309329062700272</left_val>
+ <right_val>0.5695425868034363</right_val></_></_>
+ <_>
+ <!-- tree 8 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>7 0 6 17 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-1.5127769438549876e-003</threshold>
+ <left_val>0.2759602069854736</left_val>
+ <right_val>0.5956642031669617</right_val></_></_>
+ <_>
+ <!-- tree 9 -->
+ <_>
+ <!-- root node -->
+ <feature>
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+ <_>9 0 6 4 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-0.0101574398577213</threshold>
+ <left_val>0.1732538044452667</left_val>
+ <right_val>0.5522047281265259</right_val></_></_>
+ <_>
+ <!-- tree 10 -->
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+ <!-- root node -->
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+ <tilted>0</tilted></feature>
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+ <left_val>0.1339409947395325</left_val>
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+ <_>
+ <!-- tree 11 -->
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+ <_>
+ <!-- tree 12 -->
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+ <left_val>0.0912110507488251</left_val>
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+ <left_val>0.5953313708305359</left_val>
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+ <_>
+ <!-- tree 15 -->
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+ <left_val>0.1844065934419632</left_val>
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+ <!-- tree 16 -->
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+ <left_val>0.3594244122505188</left_val>
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+ <stage_threshold>9.4985427856445313</stage_threshold>
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+ <next>-1</next></_>
+ <_>
+ <!-- stage 3 -->
+ <trees>
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+ <!-- root node -->
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+ <left_val>0.1415266990661621</left_val>
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+ <threshold>-1.2748669541906565e-004</threshold>
+ <left_val>0.6191074252128601</left_val>
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+ <left_val>0.4738228023052216</left_val>
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+ <stage_threshold>105.7611007690429700</stage_threshold>
+ <parent>20</parent>
+ <next>-1</next></_></stages></haarcascade_frontalface_alt>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_frontalface_alt2.xml b/haarcascades/haarcascade_frontalface_alt2.xml
new file mode 100644
index 0000000..caa86f6
--- /dev/null
+++ b/haarcascades/haarcascade_frontalface_alt2.xml
@@ -0,0 +1,23550 @@
+<?xml version="1.0"?>
+<!--
+ Tree-based 20x20 gentle adaboost frontal face detector.
+ Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+ IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+ By downloading, copying, installing or using the software you agree to this license.
+ If you do not agree to this license, do not download, install,
+ copy or use the software.
+
+
+ Intel License Agreement
+ For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistribution's of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistribution's in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * The name of Intel Corporation may not be used to endorse or promote products
+ derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<haarcascade_frontalface_alt2 type_id="opencv-haar-classifier">
+ <size>20 20</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
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+ <!-- root node -->
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+ <threshold>4.3272329494357109e-003</threshold>
+ <left_val>0.0383819006383419</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <threshold>0.0130761601030827</threshold>
+ <left_val>0.8965256810188294</left_val>
+ <right_val>0.2629314064979553</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
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+ <left_val>0.1021663025021553</left_val>
+ <right_node>1</right_node></_>
+ <_>
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+ <left_val>0.1238401979207993</left_val>
+ <right_val>0.6910383105278015</right_val></_></_>
+ <_>
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+ <threshold>-9.2708261217921972e-004</threshold>
+ <left_node>1</left_node>
+ <right_val>0.1953697055578232</right_val></_>
+ <_>
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+ <threshold>3.3989109215326607e-004</threshold>
+ <left_val>0.2101441025733948</left_val>
+ <right_val>0.8258674740791321</right_val></_></_></trees>
+ <stage_threshold>0.3506923019886017</stage_threshold>
+ <parent>-1</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 1 -->
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+ <_>
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+ <left_val>0.3849678933620453</left_val>
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+ <_>
+ <!-- node 1 -->
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+ <!-- tree 8 -->
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+ <!-- root node -->
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+ <left_val>0.4104770123958588</left_val>
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+ <!-- node 1 -->
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+ <left_val>0.7239024043083191</left_val>
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+ <!-- tree 9 -->
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+ <!-- root node -->
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+ <left_val>0.5640516281127930</left_val>
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+ <_>
+ <!-- node 1 -->
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+ <left_val>0.5947548151016235</left_val>
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+ <!-- tree 10 -->
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+ <left_val>0.6603232026100159</left_val>
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+ <_>
+ <!-- node 1 -->
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+ <left_val>0.4680665135383606</left_val>
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+ <!-- tree 11 -->
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+ <left_val>0.5298851132392883</left_val>
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+ <!-- node 1 -->
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+ <!-- tree 12 -->
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+ <left_val>0.1380645930767059</left_val>
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+ <!-- node 1 -->
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+ <!-- tree 13 -->
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+ <!-- node 1 -->
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+ <left_val>0.5240166187286377</left_val>
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+ <stage_threshold>5.9844889640808105</stage_threshold>
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+ <!-- stage 3 -->
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+ <!-- node 1 -->
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+ <left_val>0.2299380004405975</left_val>
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+ <!-- tree 1 -->
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+ <_>
+ <!-- node 1 -->
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+ <left_val>0.2036858946084976</left_val>
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+ <_>
+ <!-- tree 2 -->
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+ <left_val>0.2049895972013474</left_val>
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+ <!-- node 1 -->
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+ <!-- tree 3 -->
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+ <left_val>0.3045149147510529</left_val>
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+ <left_val>0.3658036887645721</left_val>
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+ <right_val>0.3008632957935333</right_val></_></_></trees>
+ <stage_threshold>32.6471290588378910</stage_threshold>
+ <parent>10</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 12 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
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+ <threshold>2.4914839304983616e-003</threshold>
+ <left_val>0.3422389030456543</left_val>
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+ <_>
+ <!-- node 1 -->
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+ <threshold>-0.0504885986447334</threshold>
+ <left_val>0.7703458070755005</left_val>
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+ <_>
+ <!-- tree 1 -->
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+ <!-- root node -->
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+ <_>9 3 2 14 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-7.7838351717218757e-004</threshold>
+ <left_node>1</left_node>
+ <right_val>0.3256342113018036</right_val></_>
+ <_>
+ <!-- node 1 -->
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+ <threshold>2.3572890495415777e-004</threshold>
+ <left_val>0.3406555950641632</left_val>
+ <right_val>0.5897027254104614</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
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+ <tilted>0</tilted></feature>
+ <threshold>4.5575071126222610e-003</threshold>
+ <left_val>0.4306578934192658</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <left_val>0.7149587273597717</left_val>
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+ <_>
+ <!-- tree 3 -->
+ <_>
+ <!-- root node -->
+ <feature>
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+ <_>9 9 2 2 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-4.4612158671952784e-004</threshold>
+ <left_val>0.3295974135398865</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <left_val>0.5845620036125183</left_val>
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+ <_>
+ <!-- tree 4 -->
+ <_>
+ <!-- root node -->
+ <feature>
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+ <_>3 4 9 1 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>7.1604831646254752e-006</threshold>
+ <left_val>0.4081954956054688</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <threshold>-3.8497708737850189e-004</threshold>
+ <left_val>0.4203113019466400</left_val>
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+ <_>
+ <!-- tree 5 -->
+ <_>
+ <!-- root node -->
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+ <left_val>0.3942466974258423</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <_>
+ <!-- tree 6 -->
+ <_>
+ <!-- root node -->
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+ <threshold>8.3513697609305382e-004</threshold>
+ <left_val>0.3026031851768494</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <left_val>0.6032196283340454</left_val>
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+ <!-- tree 7 -->
+ <_>
+ <!-- root node -->
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+ <left_node>1</left_node>
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+ <_>
+ <!-- node 1 -->
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+ <_>
+ <!-- tree 8 -->
+ <_>
+ <!-- root node -->
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+ <threshold>-7.0348767621908337e-005</threshold>
+ <left_node>1</left_node>
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+ <_>
+ <!-- node 1 -->
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+ <left_val>0.2746109068393707</left_val>
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+ <_>
+ <!-- tree 9 -->
+ <_>
+ <!-- root node -->
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+ <_>
+ <!-- node 1 -->
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+ <_>
+ <!-- tree 10 -->
+ <_>
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+ <left_val>0.3306862115859985</left_val>
+ <right_node>1</right_node></_>
+ <_>
+ <!-- node 1 -->
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+ <_>
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+ <left_node>1</left_node>
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+ <_>
+ <!-- node 1 -->
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+ <!-- tree 12 -->
+ <_>
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+ <_>
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+ <!-- node 1 -->
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+ <left_val>0.6475545167922974</left_val>
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+ <left_val>0.6929240822792053</left_val>
+ <right_val>0.4778220057487488</right_val></_></_></trees>
+ <stage_threshold>53.7555694580078130</stage_threshold>
+ <parent>18</parent>
+ <next>-1</next></_></stages></haarcascade_frontalface_alt2>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_frontalface_alt_tree.xml b/haarcascades/haarcascade_frontalface_alt_tree.xml
new file mode 100644
index 0000000..ff638d5
--- /dev/null
+++ b/haarcascades/haarcascade_frontalface_alt_tree.xml
@@ -0,0 +1,103493 @@
+<?xml version="1.0"?>
+<!--
+ Stump-based 20x20 gentle adaboost frontal face detector.
+ This detector uses tree of stage classifiers instead of a cascade
+ Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+ IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+ By downloading, copying, installing or using the software you agree to this license.
+ If you do not agree to this license, do not download, install,
+ copy or use the software.
+
+
+ Intel License Agreement
+ For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistribution's of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistribution's in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * The name of Intel Corporation may not be used to endorse or promote products
+ derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<haarcascade_frontalface_tree_alt type_id="opencv-haar-classifier">
+ <size>20 20</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>2 7 14 4 -1.</_>
+ <_>2 9 14 2 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>3.7895569112151861e-003</threshold>
+ <left_val>-0.9294580221176148</left_val>
+ <right_val>0.6411985158920288</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
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+ <!-- tree 2 -->
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+ <stage_threshold>-1.3442519903182983</stage_threshold>
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+ <left_val>-0.8594707250595093</left_val>
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+ <left_val>-0.6001418232917786</left_val>
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+ <!-- tree 6 -->
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+ <stage_threshold>-1.6378560066223145</stage_threshold>
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+ <left_val>-1.4306739903986454e-003</left_val>
+ <right_val>0.6388527154922485</right_val></_></_></trees>
+ <stage_threshold>-1.1700680255889893</stage_threshold>
+ <parent>45</parent>
+ <next>-1</next></_></stages></haarcascade_frontalface_tree_alt>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_frontalface_default.xml b/haarcascades/haarcascade_frontalface_default.xml
new file mode 100644
index 0000000..8dff079
--- /dev/null
+++ b/haarcascades/haarcascade_frontalface_default.xml
@@ -0,0 +1,35712 @@
+<?xml version="1.0"?>
+<!--
+ Stump-based 24x24 discrete(?) adaboost frontal face detector.
+ Created by Rainer Lienhart.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+ IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+ By downloading, copying, installing or using the software you agree to this license.
+ If you do not agree to this license, do not download, install,
+ copy or use the software.
+
+
+ Intel License Agreement
+ For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistribution's of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistribution's in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * The name of Intel Corporation may not be used to endorse or promote products
+ derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+-->
+<opencv_storage>
+<haarcascade_frontalface_default type_id="opencv-haar-classifier">
+ <size>24 24</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
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+ <threshold>-0.0315119996666908</threshold>
+ <left_val>2.0875380039215088</left_val>
+ <right_val>-2.2172100543975830</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
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+ <threshold>0.0123960003256798</threshold>
+ <left_val>-1.8633940219879150</left_val>
+ <right_val>1.3272049427032471</right_val></_></_>
+ <_>
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+ <left_val>-1.5105249881744385</left_val>
+ <right_val>1.0625729560852051</right_val></_></_>
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+ <right_val>1.1760339736938477</right_val></_></_>
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+ <right_val>1.2608419656753540</right_val></_></_>
+ <_>
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+ <_>
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+ <stage_threshold>-5.0425500869750977</stage_threshold>
+ <parent>-1</parent>
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+ <stage_threshold>-2.9928278923034668</stage_threshold>
+ <parent>23</parent>
+ <next>-1</next></_></stages></haarcascade_frontalface_default>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_fullbody.xml b/haarcascades/haarcascade_fullbody.xml
new file mode 100644
index 0000000..f1eaf5b
--- /dev/null
+++ b/haarcascades/haarcascade_fullbody.xml
@@ -0,0 +1,18118 @@
+<?xml version="1.0"?>
+<!--
+ 14x28 fullbody detector (see the detailed description below).
+
+//////////////////////////////////////////////////////////////////////////
+| Contributors License Agreement
+| IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+| By downloading, copying, installing or using the software you agree
+| to this license.
+| If you do not agree to this license, do not download, install,
+| copy or use the software.
+|
+| Copyright (c) 2004, Hannes Kruppa and Bernt Schiele (ETH Zurich, Switzerland).
+| All rights reserved.
+|
+| Redistribution and use in source and binary forms, with or without
+| modification, are permitted provided that the following conditions are
+| met:
+|
+| * Redistributions of source code must retain the above copyright
+| notice, this list of conditions and the following disclaimer.
+| * Redistributions in binary form must reproduce the above
+| copyright notice, this list of conditions and the following
+| disclaimer in the documentation and/or other materials provided
+| with the distribution.
+| * The name of Contributor may not used to endorse or promote products
+| derived from this software without specific prior written permission.
+|
+| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+| "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+| LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+| A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+| CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+| EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+| PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+| PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+| LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+| NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
+| Top
+//////////////////////////////////////////////////////////////////////////
+
+"Haar"-based Detectors For Pedestrian Detection
+===============================================
+by Hannes Kruppa and Bernt Schiele, ETH Zurich, Switzerland
+
+This archive provides the following three detectors:
+- upper body detector (most fun, useful in many scenarios!)
+- lower body detector
+- full body detector
+
+These detectors have been successfully applied to pedestrian detection
+in still images. They can be directly passed as parameters to the
+program HaarFaceDetect.
+NOTE: These detectors deal with frontal and backside views but not
+with side views (also see "Known limitations" below).
+
+RESEARCHERS:
+If you are using any of the detectors or involved ideas please cite
+this paper (available at www.vision.ethz.ch/publications/):
+
+@InProceedings{Kruppa03-bmvc,
+ author = "Hannes Kruppa, Modesto Castrillon-Santana and Bernt Schiele",
+ title = "Fast and Robust Face Finding via Local Context."
+ booktitle = "Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance"
+ year = "2003",
+ month = "October"
+}
+
+COMMERCIAL:
+If you have any commercial interest in this work please contact
+hkruppa@inf.ethz.ch
+
+
+ADDITIONAL INFORMATION
+======================
+Check out the demo movie, e.g. using mplayer or any (Windows/Linux-) player
+that can play back .mpg movies.
+Under Linux that's:
+> ffplay demo.mpg
+or:
+> mplayer demo.mpg
+
+The movie shows a person walking towards the camera in a realistic
+indoor setting. Using ffplay or mplayer you can pause and continue the
+movie by pressing the space bar.
+
+Detections coming from the different detectors are visualized using
+different line styles:
+upper body : dotted line
+lower body : dashed line
+full body : solid line
+
+You will notice that successful detections containing the target do
+not sit tightly on the body but also include some of the background
+left and right. This is not a bug but accurately reflects the
+employed training data which also includes portions of the background
+to ensure proper silhouette representation. If you want to get a
+feeling for the training data check out the CBCL data set:
+http://www.ai.mit.edu/projects/cbcl/software-datasets/PedestrianData.html
+
+There is also a small number of false alarms in this sequence.
+NOTE: This is per frame detection, not tracking (which is also one of
+the reasons why it is not mislead by the person's shadow on the back
+wall).
+
+On an Intel Xeon 1.7GHz machine the detectors operate at something
+between 6Hz to 14 Hz (on 352 x 288 frames per second) depending on the
+detector. The detectors work as well on much lower image resolutions
+which is always an interesting possibility for speed-ups or
+"coarse-to-fine" search strategies.
+
+Additional information e.g. on training parameters, detector
+combination, detecting other types of objects (e.g. cars) etc. is
+available in my PhD thesis report (available end of June). Check out
+www.vision.ethz.ch/kruppa/
+
+
+KNOWN LIMITATIONS
+==================
+1) the detectors only support frontal and back views but not sideviews.
+ Sideviews are trickier and it makes a lot of sense to include additional
+ modalities for their detection, e.g. motion information. I recommend
+ Viola and Jones' ICCV 2003 paper if this further interests you.
+
+2) dont expect these detectors to be as accurate as a frontal face detector.
+ A frontal face as a pattern is pretty distinct with respect to other
+ patterns occuring in the world (i.e. image "background"). This is not so
+ for upper, lower and especially full bodies, because they have to rely
+ on fragile silhouette information rather than internal (facial) features.
+ Still, we found especially the upper body detector to perform amazingly well.
+ In contrast to a face detector these detectors will also work at very low
+ image resolutions
+
+Acknowledgements
+================
+Thanks to Martin Spengler, ETH Zurich, for providing the demo movie.
+-->
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+ <stage_threshold>-30.8048992156982420</stage_threshold>
+ <parent>28</parent>
+ <next>-1</next></_></stages></haarcascade_fullbody>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_lowerbody.xml b/haarcascades/haarcascade_lowerbody.xml
new file mode 100644
index 0000000..56fb489
--- /dev/null
+++ b/haarcascades/haarcascade_lowerbody.xml
@@ -0,0 +1,15085 @@
+<?xml version="1.0"?>
+<!--
+ 19x23 lowerbody detector (see the detailed description below).
+
+//////////////////////////////////////////////////////////////////////////
+| Contributors License Agreement
+| IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+| By downloading, copying, installing or using the software you agree
+| to this license.
+| If you do not agree to this license, do not download, install,
+| copy or use the software.
+|
+| Copyright (c) 2004, Hannes Kruppa and Bernt Schiele (ETH Zurich, Switzerland).
+| All rights reserved.
+|
+| Redistribution and use in source and binary forms, with or without
+| modification, are permitted provided that the following conditions are
+| met:
+|
+| * Redistributions of source code must retain the above copyright
+| notice, this list of conditions and the following disclaimer.
+| * Redistributions in binary form must reproduce the above
+| copyright notice, this list of conditions and the following
+| disclaimer in the documentation and/or other materials provided
+| with the distribution.
+| * The name of Contributor may not used to endorse or promote products
+| derived from this software without specific prior written permission.
+|
+| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+| "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+| LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+| A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+| CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+| EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+| PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+| PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+| LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+| NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
+| Top
+//////////////////////////////////////////////////////////////////////////
+
+"Haar"-based Detectors For Pedestrian Detection
+===============================================
+by Hannes Kruppa and Bernt Schiele, ETH Zurich, Switzerland
+
+This archive provides the following three detectors:
+- upper body detector (most fun, useful in many scenarios!)
+- lower body detector
+- full body detector
+
+These detectors have been successfully applied to pedestrian detection
+in still images. They can be directly passed as parameters to the
+program HaarFaceDetect.
+NOTE: These detectors deal with frontal and backside views but not
+with side views (also see "Known limitations" below).
+
+RESEARCHERS:
+If you are using any of the detectors or involved ideas please cite
+this paper (available at www.vision.ethz.ch/publications/):
+
+@InProceedings{Kruppa03-bmvc,
+ author = "Hannes Kruppa, Modesto Castrillon-Santana and Bernt Schiele",
+ title = "Fast and Robust Face Finding via Local Context."
+ booktitle = "Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance"
+ year = "2003",
+ month = "October"
+}
+
+COMMERCIAL:
+If you have any commercial interest in this work please contact
+hkruppa@inf.ethz.ch
+
+
+ADDITIONAL INFORMATION
+======================
+Check out the demo movie, e.g. using mplayer or any (Windows/Linux-) player
+that can play back .mpg movies.
+Under Linux that's:
+> ffplay demo.mpg
+or:
+> mplayer demo.mpg
+
+The movie shows a person walking towards the camera in a realistic
+indoor setting. Using ffplay or mplayer you can pause and continue the
+movie by pressing the space bar.
+
+Detections coming from the different detectors are visualized using
+different line styles:
+upper body : dotted line
+lower body : dashed line
+full body : solid line
+
+You will notice that successful detections containing the target do
+not sit tightly on the body but also include some of the background
+left and right. This is not a bug but accurately reflects the
+employed training data which also includes portions of the background
+to ensure proper silhouette representation. If you want to get a
+feeling for the training data check out the CBCL data set:
+http://www.ai.mit.edu/projects/cbcl/software-datasets/PedestrianData.html
+
+There is also a small number of false alarms in this sequence.
+NOTE: This is per frame detection, not tracking (which is also one of
+the reasons why it is not mislead by the person's shadow on the back
+wall).
+
+On an Intel Xeon 1.7GHz machine the detectors operate at something
+between 6Hz to 14 Hz (on 352 x 288 frames per second) depending on the
+detector. The detectors work as well on much lower image resolutions
+which is always an interesting possibility for speed-ups or
+"coarse-to-fine" search strategies.
+
+Additional information e.g. on training parameters, detector
+combination, detecting other types of objects (e.g. cars) etc. is
+available in my PhD thesis report (available end of June). Check out
+www.vision.ethz.ch/kruppa/
+
+
+KNOWN LIMITATIONS
+==================
+1) the detectors only support frontal and back views but not sideviews.
+ Sideviews are trickier and it makes a lot of sense to include additional
+ modalities for their detection, e.g. motion information. I recommend
+ Viola and Jones' ICCV 2003 paper if this further interests you.
+
+2) dont expect these detectors to be as accurate as a frontal face detector.
+ A frontal face as a pattern is pretty distinct with respect to other
+ patterns occuring in the world (i.e. image "background"). This is not so
+ for upper, lower and especially full bodies, because they have to rely
+ on fragile silhouette information rather than internal (facial) features.
+ Still, we found especially the upper body detector to perform amazingly well.
+ In contrast to a face detector these detectors will also work at very low
+ image resolutions
+
+Acknowledgements
+================
+Thanks to Martin Spengler, ETH Zurich, for providing the demo movie.
+-->
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+ <right_val>-0.0402656681835651</right_val></_></_></trees>
+ <stage_threshold>-0.9546145796775818</stage_threshold>
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+ <next>-1</next></_>
+ <_>
+ <!-- stage 6 -->
+ <trees>
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+ <!-- tree 0 -->
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+ <!-- root node -->
+ <feature>
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+ <left_val>0.4319767951965332</left_val>
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+ <_>
+ <!-- tree 1 -->
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+ <left_val>0.2711654007434845</left_val>
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+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
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+ <tilted>1</tilted></feature>
+ <threshold>0.0188525095582008</threshold>
+ <left_val>0.1554879993200302</left_val>
+ <right_val>-0.5524392724037170</right_val></_></_>
+ <_>
+ <!-- tree 3 -->
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+ <left_val>0.1527225971221924</left_val>
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+ <_>
+ <!-- tree 4 -->
+ <_>
+ <!-- root node -->
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+ <left_val>0.3472546041011810</left_val>
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+ <!-- tree 5 -->
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+ <left_val>-0.0688882768154144</left_val>
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+ <_>
+ <!-- tree 6 -->
+ <_>
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+ <left_val>0.1576687991619110</left_val>
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+ <_>
+ <!-- tree 7 -->
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+ <left_val>0.3289957940578461</left_val>
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+ <_>
+ <!-- tree 8 -->
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+ <left_val>0.1635251045227051</left_val>
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+ <_>
+ <!-- tree 9 -->
+ <_>
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+ <left_val>-0.1846437007188797</left_val>
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+ <!-- tree 10 -->
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+ <!-- tree 11 -->
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+ <!-- tree 12 -->
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+ <!-- tree 13 -->
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+ <stage_threshold>-1.1777880191802979</stage_threshold>
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+ <_>
+ <!-- stage 7 -->
+ <trees>
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+ <left_val>-0.4468241035938263</left_val>
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+ <!-- tree 1 -->
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+ <!-- tree 2 -->
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+ <left_val>0.1225932016968727</left_val>
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+ <left_val>-0.3368163108825684</left_val>
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+ <!-- tree 4 -->
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+ <right_val>-0.2340593934059143</right_val></_></_>
+ <_>
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+ <left_val>0.0920741632580757</left_val>
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+ <left_val>-0.0840759426355362</left_val>
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+ <left_val>0.0564759410917759</left_val>
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+ <left_val>0.1879636943340302</left_val>
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+ <_>
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+ <left_val>-0.0176613796502352</left_val>
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+ <left_val>-0.2937808036804199</left_val>
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+ <left_val>0.0268584899604321</left_val>
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+ <left_val>0.0672073066234589</left_val>
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+ <left_val>-0.1393160969018936</left_val>
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+ <_>
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+ <_>
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+ <left_val>0.4067063927650452</left_val>
+ <right_val>-0.0501934513449669</right_val></_></_>
+ <_>
+ <!-- tree 77 -->
+ <_>
+ <!-- root node -->
+ <feature>
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+ <_>5 2 9 20 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>0.0398915298283100</threshold>
+ <left_val>0.0372191295027733</left_val>
+ <right_val>-0.5569645166397095</right_val></_></_></trees>
+ <stage_threshold>-30.6646995544433590</stage_threshold>
+ <parent>25</parent>
+ <next>-1</next></_></stages></haarcascade_lowerbody>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_profileface.xml b/haarcascades/haarcascade_profileface.xml
new file mode 100644
index 0000000..5c0a5fd
--- /dev/null
+++ b/haarcascades/haarcascade_profileface.xml
@@ -0,0 +1,31930 @@
+<?xml version="1.0"?>
+<!--
+ 20x20 profile face detector.
+ Contributed by David Bradley from Princeton University.
+
+////////////////////////////////////////////////////////////////////////////////////////
+
+ IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+
+ By downloading, copying, installing or using the software you agree to this license.
+ If you do not agree to this license, do not download, install,
+ copy or use the software.
+
+
+ Intel License Agreement
+ For Open Source Computer Vision Library
+
+ Copyright (C) 2000, Intel Corporation, all rights reserved.
+ Third party copyrights are property of their respective owners.
+
+ Redistribution and use in source and binary forms, with or without modification,
+ are permitted provided that the following conditions are met:
+
+ * Redistribution's of source code must retain the above copyright notice,
+ this list of conditions and the following disclaimer.
+
+ * Redistribution's in binary form must reproduce the above copyright notice,
+ this list of conditions and the following disclaimer in the documentation
+ and/or other materials provided with the distribution.
+
+ * The name of Intel Corporation may not be used to endorse or promote products
+ derived from this software without specific prior written permission.
+
+ This software is provided by the copyright holders and contributors "as is" and
+ any express or implied warranties, including, but not limited to, the implied
+ warranties of merchantability and fitness for a particular purpose are disclaimed.
+ In no event shall the Intel Corporation or contributors be liable for any direct,
+ indirect, incidental, special, exemplary, or consequential damages
+ (including, but not limited to, procurement of substitute goods or services;
+ loss of use, data, or profits; or business interruption) however caused
+ and on any theory of liability, whether in contract, strict liability,
+ or tort (including negligence or otherwise) arising in any way out of
+ the use of this software, even if advised of the possibility of such damage.
+
+-->
+
+<opencv_storage>
+<haarcascade_profileface type_id="opencv-haar-classifier">
+ <size>20 20</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>8 7 2 6 -1.</_>
+ <_>8 10 2 3 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>1.1384399840608239e-003</threshold>
+ <left_val>-0.8377197980880737</left_val>
+ <right_val>0.7341383099555969</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>8 3 10 7 -1.</_>
+ <_>13 3 5 7 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-0.0113423503935337</threshold>
+ <left_val>0.6270201802253723</left_val>
+ <right_val>-0.7239630222320557</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>10 11 3 6 -1.</_>
+ <_>10 14 3 3 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>-1.1023089755326509e-003</threshold>
+ <left_val>0.3760018944740295</left_val>
+ <right_val>-0.6608840823173523</right_val></_></_></trees>
+ <stage_threshold>-1.1856809854507446</stage_threshold>
+ <parent>-1</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 1 -->
+ <trees>
+ <_>
+ <!-- tree 0 -->
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+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>10 4 8 8 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-0.0195538699626923</threshold>
+ <left_val>0.4924583137035370</left_val>
+ <right_val>-0.6339616775512695</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
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+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>5 7 5 4 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>2.2794529795646667e-003</threshold>
+ <left_val>-0.6460496783256531</left_val>
+ <right_val>0.3581846058368683</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
+ <_>
+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>8 4 6 6 -1.</_>
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+ <_>11 7 3 3 2.</_></rects>
+ <tilted>0</tilted></feature>
+ <threshold>2.4270440917462111e-003</threshold>
+ <left_val>-0.4725323021411896</left_val>
+ <right_val>0.2849431037902832</right_val></_></_>
+ <_>
+ <!-- tree 3 -->
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+ <left_val>0.1699953973293304</left_val>
+ <right_val>-0.7786815762519836</right_val></_></_>
+ <_>
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+ <tilted>0</tilted></feature>
+ <threshold>2.2895270958542824e-003</threshold>
+ <left_val>0.1555171012878418</left_val>
+ <right_val>-0.6672509908676148</right_val></_></_>
+ <_>
+ <!-- tree 5 -->
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+ <tilted>0</tilted></feature>
+ <threshold>-3.0143910553306341e-003</threshold>
+ <left_val>-0.6872130036354065</left_val>
+ <right_val>0.1460456997156143</right_val></_></_>
+ <_>
+ <!-- tree 6 -->
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+ <threshold>-0.0173990093171597</threshold>
+ <left_val>0.7252438068389893</left_val>
+ <right_val>-0.1657290011644363</right_val></_></_>
+ <_>
+ <!-- tree 7 -->
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+ <feature>
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+ <tilted>0</tilted></feature>
+ <threshold>9.0722442837432027e-004</threshold>
+ <left_val>-0.4638808071613312</left_val>
+ <right_val>0.2360499948263168</right_val></_></_>
+ <_>
+ <!-- tree 8 -->
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+ <tilted>0</tilted></feature>
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+ <left_val>-0.7595962882041931</left_val>
+ <right_val>0.1143691986799240</right_val></_></_>
+ <_>
+ <!-- tree 9 -->
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+ <tilted>0</tilted></feature>
+ <threshold>0.1080468967556953</threshold>
+ <left_val>-0.1286551952362061</left_val>
+ <right_val>0.7909234166145325</right_val></_></_>
+ <_>
+ <!-- tree 10 -->
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+ <tilted>0</tilted></feature>
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+ <left_val>-0.6240354776382446</left_val>
+ <right_val>0.1484749019145966</right_val></_></_>
+ <_>
+ <!-- tree 11 -->
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+ <threshold>-0.0205713901668787</threshold>
+ <left_val>0.4080848991870880</left_val>
+ <right_val>-0.2128700017929077</right_val></_></_></trees>
+ <stage_threshold>-1.4913179874420166</stage_threshold>
+ <parent>0</parent>
+ <next>-1</next></_>
+ <_>
+ <!-- stage 2 -->
+ <trees>
+ <_>
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+ <!-- root node -->
+ <feature>
+ <rects>
+ <_>10 5 8 6 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>-0.0368992090225220</threshold>
+ <left_val>0.5330861806869507</left_val>
+ <right_val>-0.4087265133857727</right_val></_></_>
+ <_>
+ <!-- tree 1 -->
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+ <feature>
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+ <_>7 8 9 6 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>2.4960909504443407e-003</threshold>
+ <left_val>-0.6948931217193604</left_val>
+ <right_val>0.2712517976760864</right_val></_></_>
+ <_>
+ <!-- tree 2 -->
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+ <_>5 8 6 6 -1.</_>
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+ <tilted>0</tilted></feature>
+ <threshold>2.4068039783742279e-004</threshold>
+ <left_val>-0.5620825290679932</left_val>
+ <right_val>0.2193035036325455</right_val></_></_>
+ <_>
+ <!-- tree 3 -->
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+ <tilted>0</tilted></feature>
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+ <left_val>0.6906061768531799</left_val>
+ <right_val>-0.1508214026689529</right_val></_></_>
+ <_>
+ <!-- tree 4 -->
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+ <tilted>0</tilted></feature>
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+ <left_val>0.1392538994550705</left_val>
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+ <_>
+ <!-- tree 5 -->
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+ <left_val>-0.3333317041397095</left_val>
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+ <left_val>-0.6800730228424072</left_val>
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+ <left_val>-0.3867216110229492</left_val>
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+ <_>
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+ <left_val>0.1203565970063210</left_val>
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+ <left_val>0.0135613000020385</left_val>
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+ <threshold>2.5479190517216921e-003</threshold>
+ <left_val>-0.0438243597745895</left_val>
+ <right_val>0.2215041965246201</right_val></_></_></trees>
+ <stage_threshold>-1.2739679813385010</stage_threshold>
+ <parent>24</parent>
+ <next>-1</next></_></stages></haarcascade_profileface>
+</opencv_storage>
diff --git a/haarcascades/haarcascade_upperbody.xml b/haarcascades/haarcascade_upperbody.xml
new file mode 100644
index 0000000..45eeac9
--- /dev/null
+++ b/haarcascades/haarcascade_upperbody.xml
@@ -0,0 +1,29767 @@
+<?xml version="1.0"?>
+<!--
+ 22x18 upperbody detector (see the detailed description below).
+
+//////////////////////////////////////////////////////////////////////////
+| Contributors License Agreement
+| IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+| By downloading, copying, installing or using the software you agree
+| to this license.
+| If you do not agree to this license, do not download, install,
+| copy or use the software.
+|
+| Copyright (c) 2004, Hannes Kruppa and Bernt Schiele (ETH Zurich, Switzerland).
+| All rights reserved.
+|
+| Redistribution and use in source and binary forms, with or without
+| modification, are permitted provided that the following conditions are
+| met:
+|
+| * Redistributions of source code must retain the above copyright
+| notice, this list of conditions and the following disclaimer.
+| * Redistributions in binary form must reproduce the above
+| copyright notice, this list of conditions and the following
+| disclaimer in the documentation and/or other materials provided
+| with the distribution.
+| * The name of Contributor may not used to endorse or promote products
+| derived from this software without specific prior written permission.
+|
+| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+| "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+| LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+| A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+| CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+| EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+| PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+| PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+| LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+| NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
+| Top
+//////////////////////////////////////////////////////////////////////////
+
+"Haar"-based Detectors For Pedestrian Detection
+===============================================
+by Hannes Kruppa and Bernt Schiele, ETH Zurich, Switzerland
+
+This archive provides the following three detectors:
+- upper body detector (most fun, useful in many scenarios!)
+- lower body detector
+- full body detector
+
+These detectors have been successfully applied to pedestrian detection
+in still images. They can be directly passed as parameters to the
+program HaarFaceDetect.
+NOTE: These detectors deal with frontal and backside views but not
+with side views (also see "Known limitations" below).
+
+RESEARCHERS:
+If you are using any of the detectors or involved ideas please cite
+this paper (available at www.vision.ethz.ch/publications/):
+
+@InProceedings{Kruppa03-bmvc,
+ author = "Hannes Kruppa, Modesto Castrillon-Santana and Bernt Schiele",
+ title = "Fast and Robust Face Finding via Local Context."
+ booktitle = "Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance"
+ year = "2003",
+ month = "October"
+}
+
+COMMERCIAL:
+If you have any commercial interest in this work please contact
+hkruppa@inf.ethz.ch
+
+
+ADDITIONAL INFORMATION
+======================
+Check out the demo movie, e.g. using mplayer or any (Windows/Linux-) player
+that can play back .mpg movies.
+Under Linux that's:
+> ffplay demo.mpg
+or:
+> mplayer demo.mpg
+
+The movie shows a person walking towards the camera in a realistic
+indoor setting. Using ffplay or mplayer you can pause and continue the
+movie by pressing the space bar.
+
+Detections coming from the different detectors are visualized using
+different line styles:
+upper body : dotted line
+lower body : dashed line
+full body : solid line
+
+You will notice that successful detections containing the target do
+not sit tightly on the body but also include some of the background
+left and right. This is not a bug but accurately reflects the
+employed training data which also includes portions of the background
+to ensure proper silhouette representation. If you want to get a
+feeling for the training data check out the CBCL data set:
+http://www.ai.mit.edu/projects/cbcl/software-datasets/PedestrianData.html
+
+There is also a small number of false alarms in this sequence.
+NOTE: This is per frame detection, not tracking (which is also one of
+the reasons why it is not mislead by the person's shadow on the back
+wall).
+
+On an Intel Xeon 1.7GHz machine the detectors operate at something
+between 6Hz to 14 Hz (on 352 x 288 frames per second) depending on the
+detector. The detectors work as well on much lower image resolutions
+which is always an interesting possibility for speed-ups or
+"coarse-to-fine" search strategies.
+
+Additional information e.g. on training parameters, detector
+combination, detecting other types of objects (e.g. cars) etc. is
+available in my PhD thesis report (available end of June). Check out
+www.vision.ethz.ch/kruppa/
+
+
+KNOWN LIMITATIONS
+==================
+1) the detectors only support frontal and back views but not sideviews.
+ Sideviews are trickier and it makes a lot of sense to include additional
+ modalities for their detection, e.g. motion information. I recommend
+ Viola and Jones' ICCV 2003 paper if this further interests you.
+
+2) dont expect these detectors to be as accurate as a frontal face detector.
+ A frontal face as a pattern is pretty distinct with respect to other
+ patterns occuring in the world (i.e. image "background"). This is not so
+ for upper, lower and especially full bodies, because they have to rely
+ on fragile silhouette information rather than internal (facial) features.
+ Still, we found especially the upper body detector to perform amazingly well.
+ In contrast to a face detector these detectors will also work at very low
+ image resolutions
+
+Acknowledgements
+================
+Thanks to Martin Spengler, ETH Zurich, for providing the demo movie.
+-->
+<opencv_storage>
+<haarcascade_upperbody type_id="opencv-haar-classifier">
+ <size>22 18</size>
+ <stages>
+ <_>
+ <!-- stage 0 -->
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+ <tilted>0</tilted></feature>
+ <threshold>-0.0136960297822952</threshold>
+ <left_val>0.4507646858692169</left_val>
+ <right_val>-0.4217903017997742</right_val></_></_>
+ <_>
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+ <threshold>0.0124414497986436</threshold>
+ <left_val>0.1649325042963028</left_val>
+ <right_val>-0.7479348778724670</right_val></_></_>
+ <_>
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+ <threshold>-2.7094660326838493e-003</threshold>
+ <left_val>0.3100470006465912</left_val>
+ <right_val>-0.3761714100837708</right_val></_></_>
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+ <left_val>0.7618219852447510</left_val>
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+ <left_val>0.7145937085151672</left_val>
+ <right_val>-0.1449857950210571</right_val></_></_>
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+ <left_val>0.2401147037744522</left_val>
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+ <stage_threshold>-1.1264339685440063</stage_threshold>
+ <parent>-1</parent>
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diff --git a/haarcascades/mouth.xml b/haarcascades/mouth.xml
new file mode 100755
index 0000000..ae4ee24
--- /dev/null
+++ b/haarcascades/mouth.xml
@@ -0,0 +1,21991 @@
+<?xml version="1.0"?>
+<!----------------------------------------------------------------------------
+ 25x15 Mouth detector computed with 7000 positive samples
+
+//////////////////////////////////////////////////////////////////////////
+| Contributors License Agreement
+| IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
+| By downloading, copying, installing or using the software you agree
+| to this license.
+| If you do not agree to this license, do not download, install,
+| copy or use the software.
+|
+| Copyright (c) 2006, Modesto Castrillon-Santana (IUSIANI, University of
+| Las Palmas de Gran Canaria, Spain).
+| All rights reserved.
+|
+| Redistribution and use in source and binary forms, with or without
+| modification, are permitted provided that the following conditions are
+| met:
+|
+| * Redistributions of source code must retain the above copyright
+| notice, this list of conditions and the following disclaimer.
+| * Redistributions in binary form must reproduce the above
+| copyright notice, this list of conditions and the following
+| disclaimer in the documentation and/or other materials provided
+| with the distribution.
+| * The name of Contributor may not used to endorse or promote products
+| derived from this software without specific prior written permission.
+|
+| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
+| "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
+| LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
+| A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
+| CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
+| EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
+| PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
+| PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
+| LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
+| NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
+| SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. Back to
+| Top
+//////////////////////////////////////////////////////////////////////////
+
+RESEARCH USE:
+If you are using any of the detectors or involved ideas please cite one of these papers:
+
+@ARTICLE{Castrillon07-jvci,
+ author = "Castrill\'on Santana, M. and D\'eniz Su\'arez, O. and Hern\'andez Tejera, M. and Guerra Artal, C.",
+ title = "ENCARA2: Real-time Detection of Multiple Faces at Different Resolutions in Video Streams",
+ journal = "Journal of Visual Communication and Image Representation",
+ year = "2007",
+ vol = "18",
+ issue = "2",
+ month = "April",
+ pages = "130-140"
+}
+
+@INPROCEEDINGS{Castrillon07-swb,
+ author = "Castrill\'on Santana, M. and D\'eniz Su\'arez, O. and Hern\'andez Sosa, D. and Lorenzo Navarro, J. ",
+ title = "Using Incremental Principal Component Analysis to Learn a Gender Classifier Automatically",
+ booktitle = "1st Spanish Workshop on Biometrics",
+ year = "2007",
+ month = "June",
+ address = "Girona, Spain",
+ file = F
+}
+
+A comparison of this and other face related classifiers can be found in:
+
+@InProceedings{Castrillon08a-visapp,
+ 'athor = "Modesto Castrill\'on-Santana and O. D\'eniz-Su\'arez, L. Ant\'on-Canal\'{\i}s and J. Lorenzo-Navarro",
+ title = "Face and Facial Feature Detection Evaluation"
+ booktitle = "Third International Conference on Computer Vision Theory and Applications, VISAPP08"
+ year = "2008",
+ month = "January"
+}
+
+More information can be found at http://mozart.dis.ulpgc.es/Gias/modesto_eng.html or in the papers.
+
+COMMERCIAL USE:
+If you have any commercial interest in this work please contact
+mcastrillon@iusiani.ulpgc.es
+------------------------------------------------------------------------>
+<opencv_storage>
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generated by cgit v1.2.1 (git 2.18.0) at 2024-05-18 09:52:50 +0000