Moving people detection in dynamic scenes by stereo vision

Authors:
Tao Zhuo;Yanning Zhang;Tao Yang;Xiaoqiang Zhang
Affiliations:
ShannXi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China;ShannXi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China;ShannXi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China;ShannXi Provincial Key Laboratory of Speech and Image Information Processing, School of Computer Science, Northwestern Polytechnical University, Xi'an, China
Venue:
IScIDE'11 Proceedings of the Second Sino-foreign-interchange conference on Intelligent Science and Intelligent Data Engineering
Year:
2011

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Abstract

Robust people localization on a moving robot platform is an important and challenge research topic. In this paper, we present a novel moving people detection approach and system on a mobile robot platform. The proposed method mainly contains two parts: (1) A Histograms of Oriented Gradients (HOG) based detector is adopted to detect the human candidates in the dynamic scene; (2) Geometric constraints are computed to handle the ghost problem, including the depth information from a stereo camera and the external parameters of the camera calibration. To evaluate the proposed approach, a robust people detection system is developed on a moving robot platform. Extensive experiment results with challenge indoor and outdoor scenarios demonstrate the robustness and efficiency of our approach.