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Published in:
2008 | OriginalPaper | Chapter
Robust Object Tracking by Hierarchical Association of Detection Responses
Authors : Chang Huang, Bo Wu, Ramakant Nevatia
Published in: Computer Vision – ECCV 2008
Publisher: Springer Berlin Heidelberg
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We present a detection-based three-level hierarchical association approach to robustly track multiple objects in crowded environments from a single camera. At the low level, reliable tracklets (i.e. short tracks for further analysis) are generated by linking detection responses based on conservative affinity constraints. At the middle level, these tracklets are further associated to form longer tracklets based on more complex affinity measures. The association is formulated as a MAP problem and solved by the Hungarian algorithm. At the high level, entries, exits and scene occluders are estimated using the already computed tracklets, which are used to refine the final trajectories. This approach is applied to the pedestrian class and evaluated on two challenging datasets. The experimental results show a great improvement in performance compared to previous methods.