From 7cabbe3dcaa0ef520f0caaf4009bd9add5474011 Mon Sep 17 00:00:00 2001
From: "N.N." <sevyves@users.sourceforge.net>
Date: Sat, 15 Aug 2009 12:57:31 +0000
Subject: added threshold

svn path=/trunk/externals/pix_opencv/; revision=11922
---
 haarcascades/haarcascade_upperbody.xml | 29767 +++++++++++++++++++++++++++++++
 1 file changed, 29767 insertions(+)
 create mode 100644 haarcascades/haarcascade_upperbody.xml

(limited to 'haarcascades/haarcascade_upperbody.xml')

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 -->
+      <trees>
+        <_>
+          <!-- tree 0 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>5 5 12 6 -1.</_>
+                <_>9 5 4 6 3.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.0136960297822952</threshold>
+            <left_val>0.4507646858692169</left_val>
+            <right_val>-0.4217903017997742</right_val></_></_>
+        <_>
+          <!-- tree 1 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>7 13 10 4 -1.</_>
+                <_>7 15 10 2 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>0.0124414497986436</threshold>
+            <left_val>0.1649325042963028</left_val>
+            <right_val>-0.7479348778724670</right_val></_></_>
+        <_>
+          <!-- tree 2 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>3 14 9 4 -1.</_>
+                <_>6 14 3 4 3.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-2.7094660326838493e-003</threshold>
+            <left_val>0.3100470006465912</left_val>
+            <right_val>-0.3761714100837708</right_val></_></_>
+        <_>
+          <!-- tree 3 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>15 6 5 6 -1.</_>
+                <_>15 6 5 3 2.</_></rects>
+              <tilted>1</tilted></feature>
+            <threshold>-0.1000801026821137</threshold>
+            <left_val>0.7618219852447510</left_val>
+            <right_val>-0.0745569765567780</right_val></_></_>
+        <_>
+          <!-- tree 4 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>0 1 22 14 -1.</_>
+                <_>11 1 11 14 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.2511411905288696</threshold>
+            <left_val>-0.6415402889251709</left_val>
+            <right_val>0.1513922065496445</right_val></_></_>
+        <_>
+          <!-- tree 5 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>1 11 20 4 -1.</_>
+                <_>6 11 10 4 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.1051065027713776</threshold>
+            <left_val>0.7145937085151672</left_val>
+            <right_val>-0.1449857950210571</right_val></_></_>
+        <_>
+          <!-- tree 6 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>7 6 6 5 -1.</_>
+                <_>7 6 3 5 2.</_></rects>
+              <tilted>1</tilted></feature>
+            <threshold>-0.0884480178356171</threshold>
+            <left_val>0.7577317953109741</left_val>
+            <right_val>-0.0685868933796883</right_val></_></_>
+        <_>
+          <!-- tree 7 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>5 13 12 4 -1.</_>
+                <_>11 13 6 2 2.</_>
+                <_>5 15 6 2 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>0.0108749102801085</threshold>
+            <left_val>0.1461060941219330</left_val>
+            <right_val>-0.5426371097564697</right_val></_></_>
+        <_>
+          <!-- tree 8 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>7 12 8 6 -1.</_>
+                <_>7 12 4 3 2.</_>
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+              <tilted>0</tilted></feature>
+            <threshold>0.0126905702054501</threshold>
+            <left_val>0.1167458966374397</left_val>
+            <right_val>-0.4964945912361145</right_val></_></_>
+        <_>
+          <!-- tree 9 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>20 0 2 18 -1.</_>
+                <_>20 9 2 9 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.0321983993053436</threshold>
+            <left_val>-0.3852939009666443</left_val>
+            <right_val>0.0984379723668098</right_val></_></_>
+        <_>
+          <!-- tree 10 -->
+          <_>
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+                <_>8 6 6 12 -1.</_>
+                <_>10 6 2 12 3.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-3.4077179152518511e-003</threshold>
+            <left_val>0.2520087063312531</left_val>
+            <right_val>-0.2238254994153976</right_val></_></_>
+        <_>
+          <!-- tree 11 -->
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+            <!-- root node -->
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+              <rects>
+                <_>8 5 6 6 -1.</_>
+                <_>10 5 2 6 3.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>0.0303243901580572</threshold>
+            <left_val>-0.1053444966673851</left_val>
+            <right_val>0.6573541760444641</right_val></_></_>
+        <_>
+          <!-- tree 12 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>5 15 12 2 -1.</_>
+                <_>5 16 12 1 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>4.1930507868528366e-003</threshold>
+            <left_val>0.1287239938974381</left_val>
+            <right_val>-0.5316066145896912</right_val></_></_>
+        <_>
+          <!-- tree 13 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>20 0 2 18 -1.</_>
+                <_>20 9 2 9 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>0.0805014073848724</threshold>
+            <left_val>0.0416966602206230</left_val>
+            <right_val>-0.7212303280830383</right_val></_></_>
+        <_>
+          <!-- tree 14 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>0 0 2 18 -1.</_>
+                <_>0 9 2 9 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.0348220802843571</threshold>
+            <left_val>-0.4975110888481140</left_val>
+            <right_val>0.1395993977785111</right_val></_></_>
+        <_>
+          <!-- tree 15 -->
+          <_>
+            <!-- root node -->
+            <feature>
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+                <_>13 7 6 4 -1.</_>
+                <_>13 7 6 2 2.</_></rects>
+              <tilted>1</tilted></feature>
+            <threshold>7.5519368983805180e-003</threshold>
+            <left_val>-0.0921476781368256</left_val>
+            <right_val>0.1129434034228325</right_val></_></_>
+        <_>
+          <!-- tree 16 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>2 14 7 4 -1.</_>
+                <_>2 16 7 2 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>-0.0175721403211355</threshold>
+            <left_val>-0.5678442716598511</left_val>
+            <right_val>0.0935728102922440</right_val></_></_>
+        <_>
+          <!-- tree 17 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>13 7 7 4 -1.</_>
+                <_>13 7 7 2 2.</_></rects>
+              <tilted>1</tilted></feature>
+            <threshold>5.2012042142450809e-003</threshold>
+            <left_val>-0.0792380794882774</left_val>
+            <right_val>0.0618789605796337</right_val></_></_>
+        <_>
+          <!-- tree 18 -->
+          <_>
+            <!-- root node -->
+            <feature>
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+              <tilted>0</tilted></feature>
+            <threshold>-0.0307989194989204</threshold>
+            <left_val>-0.5665851235389710</left_val>
+            <right_val>0.0952714905142784</right_val></_></_>
+        <_>
+          <!-- tree 19 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>8 4 6 10 -1.</_>
+                <_>11 4 3 5 2.</_>
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+              <tilted>0</tilted></feature>
+            <threshold>-1.3465429656207561e-003</threshold>
+            <left_val>0.2401147037744522</left_val>
+            <right_val>-0.2602663934230804</right_val></_></_></trees>
+      <stage_threshold>-1.1264339685440063</stage_threshold>
+      <parent>-1</parent>
+      <next>-1</next></_>
+    <_>
+      <!-- stage 1 -->
+      <trees>
+        <_>
+          <!-- tree 0 -->
+          <_>
+            <!-- root node -->
+            <feature>
+              <rects>
+                <_>6 8 6 10 -1.</_>
+                <_>6 8 3 5 2.</_>
+                <_>9 13 3 5 2.</_></rects>
+              <tilted>0</tilted></feature>
+            <threshold>1.9108939450234175e-003</threshold>
+            <left_val>-0.4624095857143402</left_val>
+            <right_val>0.3061217069625855</right_val></_></_>
+        <_>
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+              <tilted>0</tilted></feature>
+            <threshold>9.5464065670967102e-003</threshold>
+            <left_val>0.0919561386108398</left_val>
+            <right_val>-0.5350117087364197</right_val></_></_>
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+            <threshold>-0.0434028096497059</threshold>
+            <left_val>0.5681784152984619</left_val>
+            <right_val>-0.1128493025898933</right_val></_></_>
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+            <left_val>-0.0803169310092926</left_val>
+            <right_val>0.7352185845375061</right_val></_></_>
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+              <tilted>1</tilted></feature>
+            <threshold>-6.8480317713692784e-004</threshold>
+            <left_val>0.2579864859580994</left_val>
+            <right_val>-0.2804940938949585</right_val></_></_>
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+          <!-- tree 5 -->
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+            <!-- root node -->
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+            <threshold>0.1154804974794388</threshold>
+            <left_val>0.0920655727386475</left_val>
+            <right_val>-0.7555689215660095</right_val></_></_>
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+              <tilted>0</tilted></feature>
+            <threshold>-1.9348369678482413e-003</threshold>
+            <left_val>0.2944079041481018</left_val>
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+            <!-- root node -->
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+            <threshold>-0.0435288101434708</threshold>
+            <left_val>0.4920296967029572</left_val>
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+            <threshold>-0.0302181504666805</threshold>
+            <left_val>0.7722792029380798</left_val>
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+            <threshold>0.0225508008152246</threshold>
+            <left_val>0.0692075565457344</left_val>
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+            <threshold>0.1076000034809113</threshold>
+            <left_val>0.1027851998806000</left_val>
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-- 
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