A model of binocular stereopsis including a global consistency constraint.
The binocular correspondence problem was solved by implementing the uniqueness constraint and the continuity constraint, as proposed by Marr and Poggio [Marr D, PoggioT (1976) Science 194: 283-287]. However, these constraints are not sufficient to define the proper correspondence uniquely. With these constraints, random-dot stereograms (RDSs), consisting of the periodic textures in each image, are treated as a correspondence of surfaces composed of patches of alternating values of disparity. This is quite different from the surface we perceive through the RDSs, that is a surface characterized by a single depth. Because these constraints are local, they cannot produce the global optimum of correspondence. To obtain the global optimum of correspondence, we propose a model of binocular stereopsis in which a global measure of correspondence is explicitly employed. The model consists of two hierarchical systems. First, the lower system processes various correspondences based on the uniqueness constraint. Second, the higher system provides a global measure of correspondence for the disparity in question. The higher system uniquely determines the global optimum of correspondence in the lower system through the recurrent loop between hierarchical systems. The convergence of the recurrent loop is determined by the consistency between the hierarchical systems. The condition is termed the 'global consistency constraint.
Sato
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Research Institute of Electrical Communication, Tohoku University, Sendai, Japan. satonao@riec.tohoku.ac.jp
Yano
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M
D000465:Algorithms; D003867:Depth Perception / Q000502:physiology*; D008959:Models, Neurological; D009475:Neurons, Afferent / Q000502:physiology*; D010364:Pattern Recognition, Visual / Q000502:physiology; D010507:Periodicity