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Proceedings Paper

A coarse registration method of range image based on SIFT
Author(s): Xiaoli Liu; Xiang Peng; Yongkai Yin; Jindong Tian; Ameng Li; Xiaobo Zhao
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Paper Abstract

A novel method for the coarse registration of range images is proposed. This approach is based on texture-feature recognition. As the development of optical digitizing technique, it is now able to acquire the range images and associated texture images sequentially or simultaneously. It's possible to identify the range feature points through texture feature points. Scale Invariant Feature Transform (SIFT) is an efficient method for texture feature generation. SIFT transforms texture image into a large collection of local feature vectors, each of which is invariant to image scaling, translation, and rotation. The mismatched correspondence pairs can be discarded using random sample consensus algorithm based on epipolar geometry constraint. We select more than three well-registered texture-feature pairs, with which we could find the associated range-feature pairs of the range images. Initial pose estimation of the two involved range images can be computed by these range pairs, and the fine registration is implemented using iterative closest point (ICP) algorithm. Our approach utilizes the texture information to register the range images, leading to a technique that can be automatically performed while the influence of 3D noise can be avoided. The experiment results demonstrate that the proposed approach is efficient and robust for the registration of multiple range images.

Paper Details

Date Published: 28 November 2007
PDF: 8 pages
Proc. SPIE 6833, Electronic Imaging and Multimedia Technology V, 68330X (28 November 2007); doi: 10.1117/12.756264
Show Author Affiliations
Xiaoli Liu, Shenzhen Univ. (China)
Tianjin Univ. (China)
Xiang Peng, Shenzhen Univ. (China)
Yongkai Yin, Shenzhen Univ. (China)
Jindong Tian, Shenzhen Univ. (China)
Ameng Li, Shenzhen Univ. (China)
Xiaobo Zhao, Shenzhen Univ. (China)


Published in SPIE Proceedings Vol. 6833:
Electronic Imaging and Multimedia Technology V
Liwei Zhou; Chung-Sheng Li; Minerva M. Yeung, Editor(s)

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