Visual algorithms for post production
ACM SIGGRAPH 2009 Courses
Intermediate view synthesis and interpolation based on disparity calibration and region segmentation
MUSP'06 Proceedings of the 6th WSEAS international conference on Multimedia systems & signal processing
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This paper presents a new algorithm for the reconstruction of intermediate views from a pair of still stereoscopic images. The algorithm is designed to address the issue of blur caused by linear filtering often employed in such reconstruction. The proposed algorithm is block-based and to reconstruct the intermediate views employs nonlinear disparity-compensated filtering by means of a winner-take-all strategy. The reconstructed image is modeled as a tiling by fixed-size blocks coming from various positions (disparity compensation) of either the left or right images, while the tiling map itself is modeled by a binary decision field. In addition to that, an observation model relating the left and right images via a disparity field, and a disparity field model are used. All models are probabilistic and are combined into a maximum a posteriori probability criterion. The intermediate intensities, disparities and the binary decision field are estimated jointly using the expectation-maximization algorithm. The new approach is compared experimentally on complex natural images with a reference block-based algorithm employing linear filtering. Although the improvements are localized and often subtle, they demonstrate that a high-quality intermediate view reconstruction for complex scenes is feasible