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he problem of analyzing sequences of images to extract three-dimensional T motion and structure has been at the heart of the research in computer vi sion for many years. It is very important since its success or failure will determine whether or not vision can be used as a sensory process in reactive systems. The considerable research interest in this field has been motivated at least by the following two points: 1. The redundancy of information contained in time-varying images can over come several difficulties encountered in interpreting a single image. 2. There are a lot of important applications including automatic vehicle driv ing, traffic control, aerial surveillance, medical inspection and global model construction. However, there are many new problems which should be solved: how to effi ciently process the abundant information contained in time-varying images, how to model the change between images, how to model the uncertainty inherently associated with the imaging system and how to solve inverse problems which are generally ill-posed. There are of course many possibilities for attacking these problems and many more remain to be explored. We discuss a few of them in this book based on work carried out during the last five years in the Computer Vision and Robotics Group at INRIA (Institut National de Recherche en Informatique et en Automatique).
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