Mr. Xingfang Zhou Profile

Xingfang Zhou

at Beijing Jiaotong University

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Proceedings Article | 5 March 2018 Paper

Railway clearance intrusion detection method with binocular stereo vision

Xingfang Zhou, Baoqing Guo, Wei Wei

Proceedings Volume 10710, 1071012 (2018) https://doi.org/10.1117/12.2315784

KEYWORDS: Cameras, Calibration, 3D image reconstruction, 3D modeling, 3D image processing, Computer intrusion detection, Clouds, Stereo vision systems, 3D vision, 3D acquisition

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In the stage of railway construction and operation, objects intruding railway clearance greatly threaten the safety of railway operation. Real-time intrusion detection is of great importance. For the shortcomings of depth insensitive and shadow interference of single image method, an intrusion detection method with binocular stereo vision is proposed to reconstruct the 3D scene for locating the objects and judging clearance intrusion. The binocular cameras are calibrated with Zhang Zhengyou’s method. In order to improve the 3D reconstruction speed, a suspicious region is firstly determined by background difference method of a single camera’s image sequences. The image rectification, stereo matching and 3D reconstruction process are only executed when there is a suspicious region. A transformation matrix from Camera Coordinate System(CCS) to Track Coordinate System(TCS) is computed with gauge constant and used to transfer the 3D point clouds into the TCS, then the 3D point clouds are used to calculate the object position and intrusion in TCS. The experiments in railway scene show that the position precision is better than 10mm. It is an effective way for clearance intrusion detection and can satisfy the requirement of railway application.

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