Tracking multiple mouse contours (without too many samples).

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Computer Vision and Pattern Recognition. 2005 Jul;:1039-46

Tracking multiple mouse contours (without too many samples). Branson Lab

Branson K, Belongie S

Note: Research in this publication was not performed at Janelia.

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Abstract

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 multi-target 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.

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Tracking multiple mouse contours (without too many samples).

Note: Research in this publication was not performed at Janelia.

Abstract