Covariance Descriptor Multiple Object Tracking and Re-identification with Colorspace Evaluation (original) (raw)

2013, Lecture Notes in Computer Science

This paper addresses the multi-target tracking problem with the help of a matching method where moving objects are detected in each frame, tracked when it is possible and matched by similarity of covariance matrices when difficulties arrive. Three contributions are proposed. First, a compact vector based on color invariants and Local Binary Patterns Variance is compared to more classical features vectors. To accelerate object re-identification, our second proposal is the use of a more efficient arrangement of the covariance matrices. Finally, a multiple-target algorithm with special attention in occlusion handling, merging and separation of the targets is analyzed. Our experiments show the relevance of the method, illustrating the trade-off that has to be made between distinctiveness, invariance and compactness of the features.

Sign up for access to the world's latest research.

checkGet notified about relevant papers

checkSave papers to use in your research

checkJoin the discussion with peers

checkTrack your impact