Three-Dimensional Object Surface Reconstruction Based on Camera Calibration and SIFT

Abstract:

This paper is focused on camera calibration, image matching, both of which are the key issues in three-dimensional (3D) reconstruction. In terms of camera calibration firstly, we adopt the method based on the method proposed by Zhengyou Zhang. In addition to this, it is selective for us to deal with tangential distortion. In respect of image matching, we use the SIFT algorithm, which is invariant to image translation, scaling, rotation, and partially invariant to illumination changes and to affine or 3D projections. It performs well in the follow-up matching the corresponding points. Lastly, we perform 3D reconstruction of the surface of the target object. A Graphical User Interface is designed to help us to realize the key function of binocular stereo vision, with better visualization. Apparently, the entire GUI brings convenience to the follow-up work.

• Periodical: Applied Mechanics and Materials (Volumes 719-720)
• Pages: 1191-1197
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.719-720.1191
• Online since: January 2015
• Authors: Jun Zhang, Long Ye, Qin Zhang, Jing Ling Wang
• Keywords: Binocular Stereo Vision, Camera Calibration, Image Matching, SIFT

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