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Vision without Frames: A Semiotic Paradigm of Event Based Computer Vision

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Abstract

Conventional imagers and almost all vision processes use and rely on theories that are based on the principle of static image-frames. A frame is a 2D matrix that represents the spatial locations of intensities of a scene projected on the imager. The notion of a frame itself is so embedded in machine vision, that it is usually taken for granted that this is how biological systems store light information. This paper presents a biosinpired event-based image formation principle, which output data rely on an asynchronous acquisition process. The generated information is stored in temporal volumes, which size and information depend only on the dynamic content of observed scenes. Practical analysis of such information will shows that the processing of visual information can only be based on a semiotic process. The paper also provides a general definition of the notion of visual features as the interpretation of signs according to different possible readings of the codified visual signal.

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Authors and Affiliations

  1. Institute of Intelligent Systems and Robotics, UMR 7222, University Pierre and Marie Curie, 4 Place Jussieu, 75252, Paris CEDEX 05, France

    Ryad Benosman

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  1. Ryad Benosman
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Correspondence to Ryad Benosman.

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Benosman, R. Vision without Frames: A Semiotic Paradigm of Event Based Computer Vision. Biosemiotics 3, 1–16 (2010). https://doi.org/10.1007/s12304-009-9071-3

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  • DOI: https://doi.org/10.1007/s12304-009-9071-3

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