Three-dimensional projective invariants of points from multiple images

Xiao Chen; Jianxun Li; Zhengfu Zhu

doi:10.1117/1.3028347

1 November 2008 Three-dimensional projective invariants of points from multiple images

Xiao Chen, Jianxun Li, Zhengfu Zhu

Author Affiliations +

Optical Engineering, Vol. 47, Issue 11, 117203 (November 2008). https://doi.org/10.1117/1.3028347

Abstract

Invariance is widely used in 3-D object recognition due to its good performance on change of viewpoint. A method of computing 3-D invariants of seven points from two images is presented, which can be used to achieve reliable recognition of a 3-D object and scene. Based on the matrix representation of the projective transformation between 3-D and 2-D points, geometric invariants are derived by the determinant ratios. First, the general ratiocination about invariants is represented. Second, the general method of deriving 3-D invariants from images is proposed. Simulation results on real images show that the derived invariants remain stable and are quite robust and accurate.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Xiao Chen, Jianxun Li, and Zhengfu Zhu "Three-dimensional projective invariants of points from multiple images," Optical Engineering 47(11), 117203 (1 November 2008). https://doi.org/10.1117/1.3028347

Published: 1 November 2008

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