Title :
Spatiotemporal Stereo and Scene Flow via Stequel Matching
Author :
Sizintsev, Mikhail ; Wildes, Richard P.
Author_Institution :
Dept. of Comput. Sci. & Eng., York Univ., Toronto, ON, Canada
fDate :
6/1/2012 12:00:00 AM
Abstract :
This paper is concerned with the recovery of temporally coherent estimates of 3D structure and motion of a dynamic scene from a sequence of binocular stereo images. A novel approach is presented based on matching of spatiotemporal quadric elements (stequels) between views, as this primitive encapsulates both spatial and temporal image structure for 3D estimation. Match constraints are developed for bringing stequels into correspondence across binocular views. With correspondence established, temporally coherent disparity estimates are obtained without explicit motion recovery. Further, the matched stequels also will be shown to support direct recovery of scene flow estimates. Extensive algorithmic evaluation with ground truth data incorporated in both local and global correspondence paradigms shows the considerable benefit of using stequels as a matching primitive and its advantages in comparison to alternative methods of enforcing temporal coherence in disparity estimation. Additional experiments document the usefulness of stequel matching for 3D scene flow estimation.
Keywords :
image matching; image motion analysis; image sequences; stereo image processing; 3D scene flow estimation; 3D structure; binocular stereo image sequence; dynamic scene motion; ground truth data; image structure; scene flow estimates; spatiotemporal quadric elements; spatiotemporal stereo; stequel matching; Cameras; Estimation; Optical imaging; Pattern analysis; Spatiotemporal phenomena; Stereo vision; Three dimensional displays; Stereo; motion; quadric element; scene flow; spacetime; spatiotemporal; stequel.; Algorithms; Depth Perception; Humans; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Spatio-Temporal Analysis; Tomography, Optical Coherence; Vision, Binocular;
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
DOI :
10.1109/TPAMI.2011.202