Mr. Peng Sun Profile

Peng Sun

at Univ of Science and Technology Beijing

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Proceedings Article | 27 May 2011 Paper

Multiview photogrammetry data registration by the way of stereovision movement tracking

Peng Sun, Naiguang Lu, Boen Wang, Yimin Lin

Proceedings Volume 7997, 79971Y (2011) https://doi.org/10.1117/12.888452

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A point cloud registration method based on stereovision movement tracking is proposed in this paper. The movement tracking and analysis system is composed of a stereovision measurement system and target bars. Target bars are fixed on a structured light profile scanning system. Retro-reflect target points pasted on the bars are captured by the stereovision measurement system to compute location and orientation of the scanner. The scanner is controlled to move in the view field of the movement tracking system to complete a whole scan of the large scale object. Transformation parameters including the rotation matrixes and translation vectors between local scanning coordinate systems and the global movement tracking coordinate system are computed by tracking the retro-reflect target points. Then, local cloud data of each scan is transformed into the global tracking coordinate system which is obviously an easier registration method. Experimental system is built and experiments are carried out. A movement tracking experiment is designed to give a maximum error of movement tracking less than 0.3 millimeters. Registration algorithm is verified useful by another experiment which gives a complete profile scanning of a large scale fan blade work piece. Accuracy experiments are designed to result in an average registration error less than 0.3 millimeters and standard deviation less than 0.2 millimeters.

Proceedings Article | 28 November 2007 Paper

A robust and efficient point matching method for stereovision measurement using dynamic programming

Peng Sun, Naiguang Lu

Proceedings Volume 6834, 68342W (2007) https://doi.org/10.1117/12.756598

KEYWORDS: Computer programming, 3D metrology, Cameras, 3D image processing, Optimization (mathematics), Chromium, 3D vision, Image segmentation, Calibration, Detection and tracking algorithms

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Many vision tasks such as 3D measurement, scene reconstruction, object recognition, etc., rely on feature correspondence among images. This paper presents a novel binocular method taking full account of the causes of matching ambiguities. On the basis of rectification which increases the distribution similarity of the points from the two images, the dynamic programming technique is used to search for an optimal path with the matching fashions of the most appropriate correspondences along each scan line as its nodes, which makes a global minimization of the summation of all the intra- and inter-scan line disparity gradients. This method was applied to the 3D surface measurement for an inflatable parabolic reflector with satisfactory results despite the significantly different viewpoints and occlusion that indicates the robustness, efficiency and application feasibility in real-time measurement field of this method.

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