Development of a visual compressive trackng system enhanced by adaptive boosting

This paper presents the development of a dynamic optical tracking system based on a PTZ camera platform to stably track any selected object and keep the targeted object image in the center of video images. The system is based on the Compressive Tracking algorithm which provides dimensionality reduction to achieve real-time tracking. To enhance reliability and avoid failure due to morphological variation, disappearing and blocking of the targeted objects on image frames, the developed tracking algorithm is enhanced with an Adaptive Boosting (Ada-Boost) evaluation strategy to improve the reliability of the weak Naive Bayes classifier. Besides, a heuristic threshold is applied to select and update object templates to avoid drifting of the templates. Furthermore, potential locations of target patches are searched evenly for based on the Halton sequence. Experiments on practical scenarios demonstrate the robustness and effectiveness of the proposed scheme.