Titlebook: 3D Dynamic Scene Analysis; A Stereo Based Appro Zhengyou Zhang,Olivier Faugeras Book 1992 Springer-Verlag Berlin Heidelberg 1992 Vision.art

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https://doi.org/10.1007/978-1-4612-5981-7Up to now, we have been interested in the motion analysis of two frames in which there is only one moving object. In other words, we can solve the following two problems:

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Recursion and Recursive AlgorithmsIn this chapter, we present a system, called the ., which builds automatically and incrementally a model of an unknown environment. Since most parts of the system have been described previously, we concentrate, after a brief description of the system, on how to fuse multiple 3D frames obtained by a stereo system.

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https://doi.org/10.1007/978-94-007-4138-6ing, for example, laser and ultrasound to measure depth directly) [3.1], or with passive stereo systems (algorithms from binocular or trinocular images) [3.2-9], or even with motion stereo systems (using a moving camera under constrained motion) [3.10]. Although the work described in this monograph

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A. Ben Altabef,Silvia A. Brandánically used primitives are points, line segments or planar patches. For the correspondence problem, the reader is referred to the following chapters. Given correspondences of primitives, many methods exist to determine 3D motion.

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Designing Programs from Data Structures,eference. In traffic surveillance or aerial tracking systems, it is required to find trajectories of objects in successive views. In object manipulation, an object in the model base should be first identified in the scene that the manipulator observes. All of the above examples and many others invol

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A Structured Programming Approach to Datact. 3.2) and for eye-hand systems [11.3]. An intelligent robot system [11.4] can be decomposed into three parts: perception, intelligent decision and control, and action (see Fig. 11.1). A mobile robot must include sensing (vision, sonar) and locomotion [11.5], but we must know the relationship betw

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The Shape and Motion of the Heavens,rder to obtain robust solutions (see Chap. 5). An alternative method is to use long sequences of frames (usually fewer feature correspondences are required), as in [13.1-3]. Furthermore, one can use both more frames and more feature correspondences. In other word, one can use all the available (both

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