Disparity estimation with modeling of occlusion and object orientation

Andre Redert; Chun-Jen Tsai; Emile A. Hendriks; Aggelos K. Katsaggelos

doi:10.1117/12.298391

9 January 1998 Disparity estimation with modeling of occlusion and object orientation

Andre Redert, Chun-Jen Tsai, Emile A. Hendriks, Aggelos K. Katsaggelos

Proceedings Volume 3309, Visual Communications and Image Processing '98; (1998) https://doi.org/10.1117/12.298391
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

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.

Citation Download Citation

Andre Redert, Chun-Jen Tsai, Emile A. Hendriks, and Aggelos K. Katsaggelos "Disparity estimation with modeling of occlusion and object orientation", Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); https://doi.org/10.1117/12.298391

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