Abstract
This chapter expands the notion of hierarchy by analyzing a variety of existing and proposed hierarchical systems which at various stages match the computa- tional structure of a general computer vision task. Such systems have been based on different paradigms (Pipeline, SIMD, Multi-SIMD, MIMD, etc.), of- ten mixed in various ways. A taxonomy will be presented in order to introduce a number of different families of these machines. The taxonomy is based on two hierarchical levels: the first splits the systems into homogeneous or hetero- geneous ones according to the capability of processing modules; the second is based on the ways of coupling the modules and on the interconnection networks (tight-loose, compact-distributed, fixed-reconfigurable).
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Cantoni, V., Ferretti, M. (1994). A Taxonomy of Hierarchical Machines for Computer Vision. In: Pyramidal Architectures for Computer Vision. Advances in Computer Vision and Machine Intelligence. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-2413-7_4
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DOI: https://doi.org/10.1007/978-1-4615-2413-7_4
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