Deformable part-based tracking by coupled global and local correlation filters

• We propose a deformable part-based tracking framework based on correlation filters.
• We present a collaborative algorithm for tracking-by-detection with coupled local and global correlation filters.
• We introduce a simple yet natural model for handling scale changes.
• Our proposed tracker handles occlusion, scaling and fast motion issues better than the existing models.
• Our proposed tracker gives state-of-the-art results on two benchmark datasets while keeping the processing in real time.

Correlation filters have recently attracted attention in visual tracking due to their efficiency and high performance. However, their application to long-term tracking is somewhat limited since these trackers are not equipped with mechanisms to cope with challenging cases like partial occlusion, deformation or scale changes. In this paper, we propose a deformable part-based correlation filter tracking approach which depends on coupled interactions between a global filter and several part filters. Specifically, local filters provide an initial estimate, which is then used by the global filter as a reference to determine the final result. Then, the global filter provides a feedback to the part filters regarding their updates and the related deformation parameters. In this way, our proposed collaborative model handles not only partial occlusion but also scale changes. Experiments on two large public benchmark datasets demonstrate that our approach gives significantly better results compared with the state-of-the-art trackers.