Abstract   In this paper, we propose a new method for object tracking robust to the intersection with other objects with similar appearance and to the great rotation of the camera. The method uses 3D information of the feature points and the camera position by the image-based localization method. The movement information of the camera is used by the prediction process and the calculation process of the likelihood. Furthermore, the method extracts foreground objects by the homography transformation. The result is used by the likelihood function and by the process judging whether the target object is occluded by a background object or not. The proposed method can track the target object robustly when the camera rotates greatly and when the target object is occluded by the background object or the other object. Results are demonstrated by experiments using real videos.
['Shinji Fukui', 'Sou Hayakawa', 'Yuji Iwahori', 'Tsuyoshi Nakamura', 'Manas Kamal Bhuyan']
Particle Filter Based Tracking with Image-based Localization☆