Omnivergent Stereo

作者:Steven M. Seitz, Adam Kalai, Heung-Yeung Shum

摘要

The notion of a virtual camera 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 is 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 cameras are presented: spherical omnivergent cameras,center-strip cameras and dual-strip cameras.

论文关键词:stereo, panorama, mosaic, vergence, multiperspective imaging

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论文官网地址:https://doi.org/10.1023/A:1016342731674