3D reconstruction based on the decomposition of a matrix

Guanyong Wu; Quanbing Zhang; Nian Wang; Sui Wei

doi:10.1117/12.539017

25 September 2003 3D reconstruction based on the decomposition of a matrix

Guanyong Wu, Quanbing Zhang, Nian Wang, Sui Wei

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.

Citation Download Citation

Guanyong Wu, Quanbing Zhang, Nian Wang, and 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); https://doi.org/10.1117/12.539017

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