Visual tracking via multiple representative basic appearance models based on l 1 minimization
Proceedings of the 2012 ACM Research in Applied Computation Symposium
Multitarget tracking of pedestrians in video sequences based on particle filters
Advances in Multimedia
Soft-assigned bag of features tracking
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
A survey of appearance models in visual object tracking
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Learning structured visual dictionary for object tracking
Image and Vision Computing
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In this paper, we propose a visual tracking approach based on "bag of features" (BoF) algorithm. We randomly sample image patches within the object region in training frames for constructing two codebooks using RGB and LBP features, instead of only one codebook in traditional BoF. Tracking is accomplished by searching for the highest similarity between candidates and codebooks. Besides, updating mechanism and result refinement scheme are included in BoF tracking. We fuse patch-based approach and global template-based approach into a unified framework. Experiments demonstrate that our approach is robust in handling occlusion, scaling and rotation.