29 February 2008 Adaptive filters for depth from stereo and occlusion detection
Author Affiliations +
Abstract
In this paper we present two novel techniques developed in the context of the stereo to multi-view conversion research at Philips in support of the introduction of stereoscopic and auto-stereoscopic. First, we show that we can use a relatively simple filtering approach, based on the recently popular bilateral filters, to address the correspondence problem, which is at the heart of depth and motion estimation. The proposed recursive filter uses Gaussian kernels to filter best matches and to incorporate image-based constraints. It iteratively refines the depth values starting from a random initialization and converges in a limited number of iterations to a time-stable high-quality depth map. The second contribution of the paper is an occlusion detection method that uses robust filtering for the detection of occlusion that is primarily based on the analysis of the variation of the matching metric used in the disparity estimation process. The basic underlying ideas behind the occlusion detection method are (1) that occluded areas are highly likely to be located near image boundaries (where luminance or color changes abruptly), and (2) occluded regions are characterized by a large decrease in the quality of the matching metric across these boundaries. The two algorithms were tested on real-world stereoscopic video content showing promising results.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Faysal Boughorbel, Faysal Boughorbel, } "Adaptive filters for depth from stereo and occlusion detection", Proc. SPIE 6803, Stereoscopic Displays and Applications XIX, 68030J (29 February 2008); doi: 10.1117/12.766452; https://doi.org/10.1117/12.766452
PROCEEDINGS
10 PAGES


SHARE
Back to Top