Exploiting disparity information in visual object tracking
Olga Zoidi, Nikos Nikolaidis, Ioannis Pitas · 2012
A novel method is proposed for visual object tracking in stereo videos. The algorithm employs Local Steering Kernel features and 2-dimensional color-disparity histograms for object texture description. The proposed framework requires no information about the intrinsic and extrinsic parameters of the stereo camera system. Therefore, it can be applied on 3D video content captured by commercial stereo cameras, as well as 3D movies and 3D TV programs. Experiments showed that the proposed method is effective in tracking objects under partial occlusion and changes in the object view angle.