TY - CONF T1 - Robust Bayesian cameras motion estimation using random sampling T2 - Image Processing, 2004. ICIP '04. 2004 International Conference on Y1 - 2004 A1 - Qian, G. A1 - Chellapa, Rama A1 - Qinfen Zheng KW - 3D KW - baseline KW - Bayesian KW - CAMERAS KW - cameras; KW - coarse-to-fine KW - consensus KW - density KW - estimation; KW - feature KW - function; KW - hierarchy KW - image KW - images; KW - importance KW - matching; KW - MOTION KW - posterior KW - probability KW - probability; KW - processing; KW - random KW - RANSAC; KW - real KW - realistic KW - sample KW - sampling; KW - scheme; KW - sequences; KW - stereo KW - strategy; KW - synthetic KW - wide AB - In this paper, we propose an algorithm for robust 3D motion estimation of wide baseline cameras from noisy feature correspondences. The posterior probability density function of the camera motion parameters is represented by weighted samples. The algorithm employs a hierarchy coarse-to-fine strategy. First, a coarse prior distribution of camera motion parameters is estimated using the random sample consensus scheme (RANSAC). Based on this estimate, a refined posterior distribution of camera motion parameters can then be obtained through importance sampling. Experimental results using both synthetic and real image sequences indicate the efficacy of the proposed algorithm. JA - Image Processing, 2004. ICIP '04. 2004 International Conference on VL - 2 M3 - 10.1109/ICIP.2004.1419754 ER -