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Proceedings Paper

Disparity estimation with modeling of occlusion and object orientation
Author(s): Andre Redert; Chun-Jen Tsai; Emile A. Hendriks; Aggelos K. Katsaggelos
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Paper Abstract

Stereo matching is fundamental to applications such as 3D 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.

Paper Details

Date Published: 9 January 1998
PDF: 11 pages
Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); doi: 10.1117/12.298391
Show Author Affiliations
Andre Redert, Delft Univ. of Technology (Netherlands)
Chun-Jen Tsai, Northwestern Univ. (United States)
Emile A. Hendriks, Delft Univ. of Technology (Netherlands)
Aggelos K. Katsaggelos, Northwestern Univ. (United States)


Published in SPIE Proceedings Vol. 3309:
Visual Communications and Image Processing '98
Sarah A. Rajala; Majid Rabbani, Editor(s)

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