Centralized and distributed multi-view correspondence

A probabilistic algorithm is presented for finding correspondences across multiple images in systems with large numbers of cameras and considerable overlap. The algorithm employs the theory of random graphs to provide an efficient probabilistic algorithm that performs Wide-baseline Stereo (WBS) comparisons on a small number of image pairs, and then propagates correspondence information among the cameras. A concrete mathematical analysis of its performance is given. The algorithm is extended to handle false-positive and false-negative failures of the WBS computations. We characterize the detectability of the existence of such failures, and propose an efficient method for this detection. Based on this, we propose a heuristic method for discarding false matches, and demonstrate its effectiveness in reducing errors. Since in many multi-camera applications cameras are attached to processors that handle local processing and communication, it is natural to consider distributed solutions that make use of the local processors and do not use a central computer. Our algorithm is especially suited to run in a distributed setting. If the local processors are sufficiently powerful, this allows an order of magnitude increase in computational efficiency. More importantly, a distributed implementation provides strong robustness guarantees, and eliminates the existence of a single point of failure that is inherent when the application is coordinated by a central computer. We show how to efficiently overcome processor crashes and communication failures with a minimal reduction in the quality of the algorithm's results.