Tracking multiple mouse contours (without too many samples)
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Tracking multiple mouse contours (without too many samples). / Branson, Kristin; Belongie, Serge.
In: Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005, 2005, p. 1039-1046.Research output: Contribution to journal › Conference article › Research › peer-review
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TY - GEN
T1 - Tracking multiple mouse contours (without too many samples)
AU - Branson, Kristin
AU - Belongie, Serge
PY - 2005
Y1 - 2005
N2 - We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob tracker with a contour tracker in a manner that keeps the required number of samples small This is a natural combination because both algorithms have complementary strengths. The multiple blob tracker uses a natural multitarget model and searches a smaller and simpler space. On the other hand, contour tracking gives more fine-tuned results and relies on cues that are available during severe occlusions. Our choice of combination of these two algorithms accentuates the advantages of each. We demonstrate good performance on challenging video of three identical mice that contains multiple instances of severe occlusion.
AB - We present a particle filtering algorithm for robustly tracking the contours of multiple deformable objects through severe occlusions. Our algorithm combines a multiple blob tracker with a contour tracker in a manner that keeps the required number of samples small This is a natural combination because both algorithms have complementary strengths. The multiple blob tracker uses a natural multitarget model and searches a smaller and simpler space. On the other hand, contour tracking gives more fine-tuned results and relies on cues that are available during severe occlusions. Our choice of combination of these two algorithms accentuates the advantages of each. We demonstrate good performance on challenging video of three identical mice that contains multiple instances of severe occlusion.
UR - http://www.scopus.com/inward/record.url?scp=33745171104&partnerID=8YFLogxK
U2 - 10.1109/CVPR.2005.349
DO - 10.1109/CVPR.2005.349
M3 - Conference article
AN - SCOPUS:33745171104
SP - 1039
EP - 1046
JO - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
JF - Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
T2 - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Y2 - 20 June 2005 through 25 June 2005
ER -
ID: 302054819