Stochastic view registration of overlapping cameras based on arbitrary motion.

Abstract

A new motion-based method is presented for automatic registration of images in multicamera systems, to permit synthesis of wide-baseline composite views. Unlike existing static-image and motion-based methods, our approach does not need any a priori information about the scene, the appearance of objects in the scene, or their motion. We introduce an entropy-based preselection of motion histories and an iterative Bayesian assignment of corresponding image areas. Finally, correlated point-histories and data-set optimization lead to the matching of the different views. The method is validated by demonstrating its successful use on several real-life indoor and outdoor stereo video image-sequence pairs.