Abstract-In this paper, we propose an approach for tracking an object of interest based on 3-D range data. We employ particle filtering and active contours to simultaneously estimate the global motion of the object and its local deformations. The proposed algorithm takes advantage of range information to deal with the challenging (but common) situation in which the tracked object disappears from the image domain entirely and reappears later. To cope with this problem, a method based on principle component analysis (PCA) of shape information is proposed. In the proposed method, if the target disappears out of frame, shape similarity energy is used to detect target candidates that match a template shape learned online from previously observed frames. Thus, we require no a priori knowledge of the target's shape. Experimental results show the practical applicability and robustness of the proposed algorithm in realistic tracking scenarios.
Particle filtering, which is one of the common methods in object tracking, is employed in REF with active contours to estimate the global motion of the objects in tracking moving vehicles based on 3D range data.
Object Tracking and Target Reacquisition Based on 3-D Range Data for Moving Vehicles
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
Computer Science Medicine Mathematics