This paper addresses the problem of Camera Tracking in virtual studio environment. The traditional camera tracking methods are vision-based or sensor-based. However, the Chroma Keying process in virtual studio requires the color cues, such as blue screen, to segment objects from mages and videos. It limits the application of vision-based tracking methods in virtual studio since the background could not provide enough feature information. Therefore, in our research, we would try to apply the SLAM (simultaneously localization and mapping) methodology from mobile robots to the camera tracking area. We describe a sensor-based SLAM extension algorithm for 2D camera tracking in virtual studio. Also a technique call Map Adjustment is proposed to increase the accuracy and efficiency of the algorithm. The simulation results would be given in the conclusion.
Keywords-SLAM, Particle Filter, Chroma Keying, Camera Trackin
