T he availability of multiple views of a scene makes possible new and exciting applications ranging from 3-D and free-viewpoint television to robust scene interpretation and object tracking. The hardware for multicamera systems is developing fast and is already being deployed for multimedia, security, and industrial applications. However, there are still some challenging issues in terms of processing, primarily due to the sheer amount of data involved when the number of cameras becomes very

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... e. It is therefore a primordial point to understand how the information is structured and how to take advantage of the inherent redundancy that results when the cameras are looking at the same scene. This article provides insights on the nature of the data in multiview imaging systems, particularly in terms of structure and coherence. Using this structure, we derive a multidimensional variational framework for the extraction of coherent regions and occlusion boundaries, which is an important issue in numerous multiview image processing applications such as view interpolation, compression, and scene understanding. SEEING IN SEVEN DIMENSIONS Our visual perception sense (i.e., our eyes) enables us to view the world in three dimensions. One might also say that time is a fourth dimension we are able to perceive. One way to understand why this is the case is to say that an eye captures two spatial dimensions describing where IEEE SIGNAL PROCESSING MAGAZINE [34]