Segmenting & estimating multiple 3-D rigid notions from 2-D point correspondences
Given the 2-D point correspondence set, which may be corrupted by both Gaussian noise and outliers, of a scene containing multiple rigid objects, and based on the rigidity constraint, the proposed algorithm, consisting of the initial partial match generation and growth, can segment the above set into several subsets corresponding to different 3-D rigid notions and outliers. The notion parameters of each rigid motion can then be obtained by the motion estimation algorithm for single 3-D rigid object. Computer simulation results demonstrate the effectiveness and efficiency of the algorithm.
Publication Source (Journal or Book title)
Zidonghua Xuebao/Acta Automatica Sinica
Liang, X., Wu, L., & Yu, J. (1998). Segmenting & estimating multiple 3-D rigid notions from 2-D point correspondences. Zidonghua Xuebao/Acta Automatica Sinica, 24 (2), 186-192. Retrieved from https://repository.lsu.edu/eecs_pubs/863