Polar Object Tracking in 360-Degree Camera Images

In this paper, a novel method for polar object tracking in output images from wide field of view of the 360-degree cameras is presented. The proposed method is based on the novel polar object selection to track various objects with diverse shapes directly in polar videos with no rectification. A highly overlapping object selection scheme is proposed for the challenging condition in the moving camera scenarios. Innovative color classifiers are proposed to better detection of desired object in the complex backgrounds. Continuous energy minimizing method is used to deal with the in-plane rotation problem. The selection of a polar area of interest is proposed to optimize the implementation cost. Moreover, the known Lukas-Kanade tracking method is exploited in parallel for further improvement of the tracking result. The experimental results demonstrate the success of the proposed method in terms of precision rate tracking the different objects in the polar images.