Three-dimensional Human Tracking of a Mobile Robot by Skeleton Extraction Using Two Cameras

―Robust Human Tracking with Tracking Return Function―

Abstract

In this paper, we propose a new human tracking method equipped with a function to return tracking a person. Under the stereo framework of fusing the processing results of two cameras, there is a three-dimensional tracking system for a specific person by a mobile robot using OpenPose that can acquire skeletal information using deep learning. We propose a new human tracking system equipped with the function to return tracking a person by template matching that limits the search range by epipolar constraint. The function is to return tracking a person who failed to be tracked by using the image information that was successfully tracked. With this function, even if one camera fails to track a person, the robot can continue to track the person. The effectiveness of the proposed human tracking system is verified by experiments.