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#X obj 282 44 declare -path ../..;
#X obj 144 284 pix_opencv_contours;
#X obj 144 404 pix_opencv_trackKnn;
#X obj 144 506 pix_texture;
#X obj 39 59 gemwin;
#X msg 39 17 create \, 1;
#X msg 46 38 destroy;
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#X msg 227 166 \$2;
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#X text 348 252 here is an example on how to display blobs with Gem
;
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#X text 253 167 <- be careful ! the size of the cvblob matrix could
change;
#X text 335 184 please check second element to gets matrix width (number
of value per blob);
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#X obj 187 13 inlet cvblob;
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#X msg 160 252 area \$1;
#X obj 144 170 pix_opencv_threshold;
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#X text 519 110 This example shows how to make a simple tracking algorithm.
;
#X text 534 134 1 First take a video source (here a video source like
a webcam);
#X text 534 164 2 process it to extract features of interessed \, here
I use a very simple (and not so accurate) gray convertion and thresholding
based on luminance. This is the binarisation stage.;
#X msg 253 252 cvblobOutput 1 \, hierarchy_level 0;
#X text 534 224 3 find blob contours. Select only blob greater than
an area threshold. Also we only get the outer contour (not the inner
holes) of the shape thanks to the [hierarchy_level 0( message.;
#X text 534 284 4 the found blobs are send to [pix_opencv_trackKnn]
to sort there id according to the Knn algorithm.;
#X text 532 322 To complete this process we could add a Kalmann filter
to forseen tracking data in case of hiding or somethign else.;
#X text 515 522 Antoine Villeret - 2013;
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