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Robustness improvement of human detecting and tracking for mobile robot

机译:改进移动机器人人体检测与跟踪的鲁棒性

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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.
机译:在本文中,我们提出了一种人类检测​​和跟踪的方法。为了提高检测和跟踪的鲁棒性和实时性,我们提出了一种基于立体视觉和EKF的自主机器人检测和跟踪方法。考虑到人体运动姿势的多样性,采用胡,虎头和肩膀的轮廓来识别人体。另外,EKF用于校正和预测人类的位置和方向,而移动机器人的自适应速度控制则用于实现对人类跟踪的鲁棒性。本文详细介绍了该方法的体系结构,并给出了一些实验结果以验证该方法的有效性。

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