25 September 2003 3D reconstruction based on the decomposition of a matrix
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Proceedings Volume 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition; (2003) https://doi.org/10.1117/12.539017
Event: Third International Symposium on Multispectral Image Processing and Pattern Recognition, 2003, Beijing, China
Abstract
This paper proposes a 3D reconstruction method based on the decomposition of matrix. The method uses the Singular Value Decomposition (SVD) of the fundamental matrix, which leads to a particularly simple form of the Kruppa equations optimized by conjugate gradient method. The derivation doesn't need the somewhat non-intuitive geometric concept of the absolute conic. After the projective depths are estimated, the non-singular 4x4 matrix is obtained to realize the Euclidean reconstruction. Experimental results demonstrate the effectiveness of the proposed method.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guanyong Wu, Guanyong Wu, Quanbing Zhang, Quanbing Zhang, Nian Wang, Nian Wang, Sui Wei, Sui Wei, } "3D reconstruction based on the decomposition of a matrix", Proc. SPIE 5286, Third International Symposium on Multispectral Image Processing and Pattern Recognition, (25 September 2003); doi: 10.1117/12.539017; https://doi.org/10.1117/12.539017
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