Probabilistic Tracking Method Based on the Spatial Bin-Ratio Information

Abstract

We proposed a new similarity measure method which could be used within the framework of probability trackers based on the particle filter to track the object. In the particle filter framework, the state transition model is chosen as the simple second-order auto-regressive mode, and the state measure is chosen as the BBRS (Blocks-Bin-Ratio-Similarity). The BBRS considers both the spatial information and the ratios between bin values of histograms. The simulation experiment was made to compare with the similarity measures based on color-histogram and the Bin-Ratio Similarity, and the tracking results in the videos showed that the BBRS-based similarity measure was more discriminative than the color histogram similarity measure in robustly tracking the object in challenging videos where the appearance and motion are drastically changing over time.

Keywords:

• BBRS
• color histogram
• particle filters
• similarity measure
• visual tracking

ACKNOWLEDGMENTS

We would like to thank the editor in chief Professor Hyungsuck Cho and the reviewers for their valuable comments during the review process, which improved the article. Research work was partially supported by the Chinese National Science Foundation (NSFC Grant No. 60903142), the Natural Science Foundation of CQ-CSTC (CSTC 2009BB3192).

Notes

¹ http://cv.snu.ac.kr/research/~vtd and http://www.eecs.qmul.ac.uk/~andrea/spevi.html.