Personfollowing for Telepresence Robots Using Web Cameras Many existing mobile robotic telepresence systems have equipped with two web cameras, one is a forwardfacing camera (FF camera) for video communication, and the other is a downwardfacing camera (DF camera) for robot navigation. In this paper, we present a new framework of autonomous personfollowing for telepresence robots using the two web cameras. Based on correlation filters tracking methods, we use the FF camera to track the upper body of a person and the DF camera to localize and track the personxe2x80x99s feet. We improve the robustness of feet trackers, consisting of a left foot tracker and a right foot tracker, by making full use of the spatial constraints of the human body parts. We conducted experiments on tracking in different environmental situations and real personfollowing scenario to evaluate the effectiveness of our method.

An Efficient HumanFollowing Method by Fusing Kernelized Correlation Filter and Depth Information for Mobile Robot Humanfollowing ability enables mobile robots to cooperate with human beings smartly. The kernelized correlation filter (KCF) was typically adopted as a human tracker during the humanfollowing process due to its advantages of fast speed and high precision. However, it is easy to drift away owing to the changes of human pose. In this study, we proposed an efficient humanfollowing method by fusion of KCF and depth information for the mobile robot. The target human was separated from the background regions based on the seeded region growing. KCF tracker outputs and segmentation results were fused by using the adaptive weighted fusion method. The weighting factors were adjusted based on the tracking quality indicators, which reflect the tracking reliability of KCF and the distribution of depth information. Experimental results verify the effectiveness of the proposed method in terms of tracking speed and stability. The center location error of all frames was less than 48 pixels and the bounding box overlap rate of all frames was larger than 0.62.