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Proceedings Paper

Week texture objects pose estimation based on 3D model
Author(s): Yang Chen; Hanmo Zhang; Shaoxiong Tian; Changxin Gao
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Paper Abstract

This paper proposes a 3D pose estimation method for week texture objects, by performing point matching of a test image to a matched rendering image of an object rather than its 3D model. Give a 3D model of an object, we use an exemplar based 2D-3D matching method to estimate the coarse pose of the object. We first obtain the 2D rendering images of each view of the object using its 3D model, and build an exemplar based model using all the rendering images. For a test image, we then perform 2D-3D matching using the proposed model, and the rendering image with the highest score is the best match to the test image. The coarse pose can be obtained using the view parameters of the rending images. Finally, we perform point matching between the matched rendering image and the test image to estimate pose more accurately. The proposed coarse-to- fine pose estimation method can provide stronger constraint, which makes pose estimation more accurate. The experimental results demonstrate the effectiveness of the proposed method.

Paper Details

Date Published: 9 April 2018
PDF: 6 pages
Proc. SPIE 10609, MIPPR 2017: Pattern Recognition and Computer Vision, 106090U (9 April 2018);
Show Author Affiliations
Yang Chen, Huazhong Univ. of Science and Technology (China)
Hanmo Zhang, Shanghai Aerospace Control Technology Institute (China)
Shaoxiong Tian, Shanghai Aerospace Control Technology Institute (China)
Changxin Gao, Huazhong Univ. of Science and Technology (China)

Published in SPIE Proceedings Vol. 10609:
MIPPR 2017: Pattern Recognition and Computer Vision
Zhiguo Cao; Yuehuang Wang; Chao Cai, Editor(s)

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