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In this paper, we compare and evaluate five contemporary, data-driven, real-time 2D object tracking methods: the region tracker by Hager et al., the Hyperplane tracker, the CONDENSATION tracker, and the Mean Shift and Trust Region trackers. The first two are classical template based methods, while the latter three are from the more recently proposed class of histogram based trackers. All trackers are evaluated for the task of pure translation tracking, as well as tracking translation plus scaling. For the evaluation, we use a publically available, labeled data set consisiting of surveillance videos of humans in public spaces. This data set demonstrates occlusions, changes in object appearance, and scaling.

A Comparative Evaluation of Template and Histogram Based 2D Tracking Algorithms