Copyright © 2008 Huan Jin and Gang Qian. This is an open access article distributed under the
Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper presents a robust real-time object tracking system for human computer interaction in mediated environments with interfering visual projection in the background. Two major
contributions are made in our research to achieve robust object tracking. A reliable outlier rejection algorithm is developed using the epipolar and homography constraints to remove false candidates caused by interfering background projections and mismatches between cameras. To reliably integrate
multiple estimates of the 3D object positions, an efficient fusion algorithm based on mean shift is used. This fusion algorithm can also reduce tracking errors caused by partial occlusion of the object in some of the camera views. Experimental results obtained in real life scenarios demonstrate that the proposed system is able to achieve decent 3D object tracking performance in the presence of interfering background
visual projection.