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Pyramidal Architectures for Computer Vision (Paperback, Softcover reprint of the original 1st ed. 1994)
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Pyramidal Architectures for Computer Vision (Paperback, Softcover reprint of the original 1st ed. 1994)
Series: Advances in Computer Vision and Machine Intelligence
Expected to ship within 10 - 15 working days
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Computer vision deals with the problem of manipulating information
contained in large quantities of sensory data, where raw data
emerge from the transducing 6 7 sensors at rates between 10 to 10
pixels per second. Conventional general purpose computers are
unable to achieve the computation rates required to op erate in
real time or even in near real time, so massively parallel systems
have been used since their conception in this important practical
application area. The development of massively parallel computers
was initially character ized by efforts to reach a speedup factor
equal to the number of processing elements (linear scaling
assumption). This behavior pattern can nearly be achieved only when
there is a perfect match between the computational struc ture or
data structure and the system architecture. The theory of
hierarchical modular systems (HMSs) has shown that even a small
number of hierarchical levels can sizably increase the
effectiveness of very large systems. In fact, in the last decade
several hierarchical architectures that support capabilities which
can overcome performances gained with the assumption of linear
scaling have been proposed. Of these architectures, the most
commonly considered in com puter vision is the one based on a very
large number of processing elements (PEs) embedded in a pyramidal
structure. Pyramidal architectures supply the same image at
different resolution lev els, thus ensuring the use of the most
appropriate resolution for the operation, task, and image at hand.
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