IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiresolution Gray-Scale and Rotation Invariant Texture Classification with Local Binary Patterns
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evaluating multiple object tracking performance: the CLEAR MOT metrics
Journal on Image and Video Processing - Regular
Multiple-Target Tracking by Spatiotemporal Monte Carlo Markov Chain Data Association
IEEE Transactions on Pattern Analysis and Machine Intelligence
Globally-optimal greedy algorithms for tracking a variable number of objects
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
Multiobject tracking as maximum weight independent set
CVPR '11 Proceedings of the 2011 IEEE Conference on Computer Vision and Pattern Recognition
IEEE Transactions on Multimedia
Tracking multiple people under global appearance constraints
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
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In this paper, we propose an improved efficient MHT algorithm integrated with HSV-LBP appearance and repulsion-inertia model for multi-object tracking. Simultaneously tracking multiple objects is critical to video content analysis and virtual reality. The main issues we want to address in this paper are integration of video image patch information into data association and ambiguous observations caused by objects in close proximity. A likelihood function of HSV-LBP histogram with strategy of template updating is constructed. A repulsion-inertia model is adopted to explore more useful information from ambiguous detections. Experimental results show that the proposed approach generates better trajectories with less missing objects and identity switches.