Range based object tracking and segmentation

We present an approach for tracking a moving object based on range information in stereoscopic temporal imagery. Range information is filtered by the proposed dynamic scheme to improve the quality of active contour segmentation, and to better estimate the global motion of the object. Region-based active contours using Bhattacharyya gradient flow is exploited due to its robustness to noise of a cluttered depth map. Such a sensor-fusion approach of an active contour segmentation of the image data with the statistics of a depth map provides a state estimate that is more accurate than what would be possible with either of the two alone. Experimental results demonstrate the applicability of the proposed method on several stereoscopic sequences.