Robustness improvement of human detecting and tracking for mobile robot

Abstract

In this paper, we presents a method of human detecting and tracking. To improve the robustness and real-time performance of detecting and tracking, we propose an autonomous robot detecting and tracking approach based on stereo vision and EKF. In view of diverse human motion posture, Hu moment of the head and shoulder contour is adopted to recognize human body. In addition, EKF is used to correct and predict human location and orientation, and an adaptive speed control for mobile robot is used to realize a robust for human tracking. This paper details the architecture of the proposed method and gives some experimental results to verify the effectiveness of the proposed method.