Real-time Vision-based Robotic Person Following in Fast Walking

The paper proposes a real-time robotic person following using a combination of shape detection and color histogram matching with the adaptation of the search area. First the person’s head is detected in the image by applying edge detection and a modified Hough transform. Next the area under the head in the image is searched for the person’s shirt color characteristics, as well as detecting the torso with a super-ellipse shape model. The search area in the image for finding the person is adaptively expanded or contracted to ensure fast computation and low false detection. The proposed image processing techniques together with the adaptation achieves a reliable real-time system for fast person following. The system has been implemented on a Segway robotic platform and results are provided.