Abstract:
Traditional stereo algorithms estimate disparity at the same resolution as the observations. In this work we address the problem of estimating disparity and occlusion inf...Show MoreMetadata
Abstract:
Traditional stereo algorithms estimate disparity at the same resolution as the observations. In this work we address the problem of estimating disparity and occlusion information at a higher resolution (HR). We draw on the image formation model from the motion super-resolution domain to relate HR disparity and the observations. This approach estimates both the HR disparity and HR intensity. We minimize a suitably constructed cost function using graph cuts and iterated conditional modes (ICM) for disparity and intensity, respectively.
Date of Conference: 08-11 December 2008
Date Added to IEEE Xplore: 23 January 2009
ISBN Information:
Print ISSN: 1051-4651