Abstract We describe a method for computing a dense estimate of motion and disparity, given a stereo video sequence containing moving non-rigid objects. In contrast to previous approaches, motion and disparity are estimated simultaneously from a single coherent probabilistic model that correctly accounts for all occlusions, depth discontinuities, and motion discontinuities. The results demonstrate that simultaneous estimation of motion and disparity is superior to estimating either in isolation, and show the promise of the technique for accurate, probabilistically justified, scene analysis.
Dense Motion and Disparity Estimation Via Loopy Belief Propagation
2006-01-01
10 pages
Article/Chapter (Book)
Electronic Resource
English
Reference Image , Object Boundary , Foreground Object , Motion Problem , Disparity Estimation Computer Science , Image Processing and Computer Vision , Computer Imaging, Vision, Pattern Recognition and Graphics , Pattern Recognition , Artificial Intelligence (incl. Robotics) , Algorithm Analysis and Problem Complexity
Dense Motion and Disparity Estimation Via Loopy Belief Propagation
British Library Conference Proceedings | 2006
|Motion estimation from disparity images
IEEE | 2001
|Motion Estimation from Disparity Images
British Library Conference Proceedings | 2001
|A Feature-based Approach for Dense Segmentation and Estimation of Large Disparity Motion
British Library Online Contents | 2006
|