Imporved method for stereo vision-based human detection for a mobile robot following a target person

South African Journal of Industrial Engineering

Ayaz, Yasar¹  Muhammad, Naveed¹  Jamil, Moshin¹  Gilani, Syed Omer¹  Ali, Badar¹ 

[1] National University of Sciences and Technologies Islamabad;

关键词: human detection;    human tracking;    service robot;    Haar cascade classifier;    Mean Shift;    LK Optical Flow;    particle filter;    Kalman filter;    stereo vision;   

DOI  :  10.7166/26-1-891

来源: DOAJ

【 摘 要 】

Interaction between humans and robots is a fundamental need for assistive and service robots. Their ability to detect and track people is a basic requirement for interaction with human beings. This article presents a new approach to human detection and targeted person tracking by a mobile robot. Our work is based on earlier methods that used stereo vision-based tracking linked directly with Hu moment-based detection. The earlier technique was based on the assumption that only one person is present in the environment – the target person – and it was not able to handle more than this one person. In our novel method, we solved this problem by using the Haar-based human detection method, and included a target person selection step before initialising tracking. Furthermore, rather than linking the Kalman filter directly with human detection, we implemented the tracking method before the Kalman filter-based estimation. We used the Pioneer 3AT robot, equipped with stereo camera and sonars, as the test platform.

【 授权许可】

Unknown