Robust Real-Time 3D Object Tracking with Interfering Background Visual Projections

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.