Title :
Spacetime stereo: shape recovery for dynamic scenes
Author :
Zhang, Li ; Curless, Brian ; Seitz, Steven M.
Author_Institution :
Dept. of Comput. Sci. & Eng., Univ. of Washington, Seattle, WA, USA
Abstract :
This paper extends the traditional binocular stereo problem into the spacetime domain, in which a pair of video streams is matched simultaneously instead of matching pairs of images frame by frame. Almost any existing stereo algorithm may be extended in this manner simply by replacing the image matching term with a spacetime term. By utilizing both spatial and temporal appearance variation, this modification reduces ambiguity and increases accuracy. Three major applications for spacetime stereo are proposed in this paper. First, spacetime stereo serves as a general framework for structured light scanning and generates high quality depth maps for static scenes. Second, spacetime stereo is effective for a class of natural scenes, such as waving trees and flowing water, which have repetitive textures and chaotic behaviors and are challenging for existing stereo algorithms. Third, the approach is one of very few existing methods that can robustly reconstruct objects that are moving and deforming over time, achieved by use of oriented spacetime windows in the matching procedure. Promising experimental results in the above three scenarios are demonstrated.
Keywords :
feature extraction; image matching; image reconstruction; stereo image processing; video signal processing; ambiguity reduction; binocular stereo problem; chaotic behavior; computer vision; deforming object; depth map generation; dynamic scene; flowing water; frame by frame matching; image matching; moving object; natural scene; object reconstruction; repetitive texture; shape estimation; shape recovery; spacetime domain; spacetime stereo; spatial appearance variation; static scene; stereo algorithm; structured light scanning; temporal appearance variation; video stream matching; waving trees; Chaos; Computer science; Image matching; Image reconstruction; Layout; Pixel; Robustness; Shape; Stereo vision; Streaming media;
Conference_Titel :
Computer Vision and Pattern Recognition, 2003. Proceedings. 2003 IEEE Computer Society Conference on
Print_ISBN :
0-7695-1900-8
DOI :
10.1109/CVPR.2003.1211492