This paper presents a new stereo algorithm for computing dense disparity maps from stereo image pairs by a global cost relaxation, realized as an optimization problem, where the disparity map is the momentary state of a dynamic process. Following the natural role model of the human visual system, we assign a set of possible disparities to each image pixel described by cooperating probability variables. In the first step a correlation-based similarity measure is performed to initialize the relaxation process. The relaxation itself is formulated as an optimization of a global cost function taking into account both the stereoscopic continuity constraint and considerations of the pixel similarity. A special formulation guarantees the existence of a unique cost minimum which can be easily and rapidly found by standard numerical procedures. In a post-processing step, occluded areas are detected and a sub-pixel precise disparity map is computed.

No abstract

No abstract

A computational approach to the perception of illusory contours is introduced. The approach is based on the tensor voting technique and applied to several real and synthetic images. Special interest is given to the design of the communication pattern for spatial contour integration, called voting field. We gratefully acknowledge partial funding of this work by the Deutsche Forschungsgemeinschaft under grant Me1289/7-1 "KomForm".

No abstract