Tracking multiple mouse contours (without too many samples)

Publikation: Bidrag til tidsskriftKonferenceartikelForskningfagfællebedømt

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.

OriginalsprogEngelsk
TidsskriftProceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Sider (fra-til)1039-1046
Antal sider8
DOI
StatusUdgivet - 2005
Eksternt udgivetJa
Begivenhed2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005 - San Diego, CA, USA
Varighed: 20 jun. 200525 jun. 2005

Konference

Konference2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
LandUSA
BySan Diego, CA
Periode20/06/200525/06/2005
SponsorIEEE Computer Society

ID: 302054819