Disparity estimation with modeling of occlusion and object orientation

André Redert*, Chun Jen Tsai, Emile Hendriks, Aggelos K. Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations


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 languageEnglish (US)
Pages (from-to)798-808
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Issue number2
StatePublished - Dec 1 1998
EventVisual Communications and Image Processing '98 - San Jose, CA, United States
Duration: Jan 28 1998Jan 30 1998

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics


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