Abstract
Stereo matching is fundamental to applications such as 3-D visual communications and depth measurements. There are several different approaches towards this objective, including feature-based methods, block-based methods, and pixel-based methods. Most approaches use regularization to obtain reliable fields. Generally speaking, when smoothing is applied to the estimated depth field, it results in a bias towards surfaces that are parallel to the image plane. This is called fronto-parallel bias. Recent pixel-based approaches claim that no disparity smoothing is necessary. In their approach, occlusions and objects are explicitly modeled. But these models interfere each others in the case of slanted objects and result in a fragmented disparity field. In this paper we propose a disparity estimation algorithm with explicit modeling of object orientation and occlusion. The algorithm incorporates adjustable resolution and accuracy. Smoothing can be applied without introducing the fronto-parallel bias. The experiments show that the algorithm is very promising.
Original language | English (US) |
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Pages (from-to) | 798-808 |
Number of pages | 11 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 3309 |
Issue number | 2 |
DOIs | |
State | Published - 1998 |
Event | Visual Communications and Image Processing '98 - San Jose, CA, United States Duration: Jan 28 1998 → Jan 30 1998 |
ASJC Scopus subject areas
- Electronic, Optical and Magnetic Materials
- Condensed Matter Physics
- Applied Mathematics
- Electrical and Electronic Engineering
- Computer Science Applications