Title :
Omnivergent stereo
Author :
Shum, Heung-Yeung ; Kalai, Adam ; Seitz, Steven M.
Author_Institution :
Vision Technol. Group, Microsoft Res., Redmond, WA, USA
Abstract :
The notion of a virtual sensor for optimal 3D reconstruction is introduced. Instead of planar perspective images that collect many rays at a fixed viewpoint, omnivergent cameras collect a small number of rays at many different viewpoints. The resulting 2D manifold of rays are arranged into two multiple-perspective images for stereo reconstruction. We call such images omnivergent images, and the process of reconstructing the scene from such images, omnivergent stereo. This procedure is shown to produce 3D scene models with minimal reconstruction error due to the fact that for any point in the 3D scene, two rays with maximum vergence angle can be found in the omnivergent images. Furthermore, omnivergent images are shown to have horizontal epipolar lines, enabling the application of traditional stereo matching algorithms, without modification. Three types of omnivergent virtual sensors are presented: spherical omnivergent cameras, center-strip cameras and dual-strip cameras
Keywords :
image matching; image reconstruction; stereo image processing; virtual reality; 2D manifold; 3D scene models; center-strip cameras; dual-strip cameras; horizontal epipolar lines; maximum vergence angle; minimal reconstruction error; multiple-perspective images; omnivergent images; omnivergent stereo; optimal 3D reconstruction; spherical omnivergent cameras; stereo matching algorithms; stereo reconstruction; virtual sensor; Application software; Cameras; Computer vision; Image reconstruction; Image representation; Image sensors; Image sequences; Layout; Stereo image processing; Stereo vision;
Conference_Titel :
Computer Vision, 1999. The Proceedings of the Seventh IEEE International Conference on
Conference_Location :
Kerkyra
Print_ISBN :
0-7695-0164-8
DOI :
10.1109/ICCV.1999.791193