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Hierarchical Strategies in Computer Vision Systems

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Pyramidal Architectures for Computer Vision

Part of the book series: Advances in Computer Vision and Machine Intelligence ((ACVM))

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Abstract

In order to achieve the high performance that real applications require, correct computation on the relevant image data at the right time is essential. Following the studies on vision and perception in humans, two phases can be distin- guished: (1) a preattentive phase, in which the visual system is only dedicated to the detection of events and regions of interest within its wide field of view, and (2) an attentive phase, in which an extensive analysis of a restricted amount of data is performed. Correspondingly, an equivalent computational paradigm will be introduced in order to reduce the huge amount of raw data transduced by a standard artificial vision sensor. Such a paradigm provides for the use of variable-resolution grids, according to the image detail required for the task, thus obtaining multiresolution systems with different-sized layers.

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Authors and Affiliations

  1. University of Pavia, Pavia, Italy

    Virginio Cantoni & Marco Ferretti

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  1. Virginio Cantoni
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  2. Marco Ferretti
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© 1994 Springer Science+Business Media New York

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Cantoni, V., Ferretti, M. (1994). Hierarchical Strategies in Computer Vision Systems. 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_2

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  • DOI: https://doi.org/10.1007/978-1-4615-2413-7_2

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  • Online ISBN: 978-1-4615-2413-7

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