Fast stereo matching using constraints in discrete space

Abstract

We present a new basis for discrete representation of stereo correspondence. This center referenced basis permits a more natural, complete and concise representation of constraints in stereo matching. In this context a MAP formulation for disparity estimation is derived and reduced to unconstrained minimization of an energy function. incorporating natural constraints, the problem is simplified to the shortest path problem in a sparsely connected trellis structure which is performed by an efficient dynamic programing algorithm. The computational complexity is the same as the best of other dynamic programming methods, but a very high degree of concurrency is possible in the algorithm making it suitable for implementation with parallel procesors. Experimental results confirm the performance of this method and matching errors are found to degrade gracefully in exponential form with respect to noise.