Cognitive vision: Integrating symbolic qualitative representations with computer vision

A. G. Cohn, D. C. Hogg, B. Bennett, V. Devin, A. Galata, D. R. Magee, C. Needham, P. Santos

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    14 Citations (Scopus)

    Abstract

    We describe the challenge of combining continuous computer vision techniques and qualitative, symbolic methods to achieve a system capable of cognitive vision. Key to a truly cognitive system, is the ability to learn: to be able to build and use models constructed autonomously from sensory input. In this paper we overview a number of steps we have taken along the route to the construction of such a system, and discuss some remaining challenges.

    Original languageEnglish
    Title of host publicationCognitive Vision Systems
    Subtitle of host publicationSampling the Spectrum of Approaches
    EditorsHenrik Christensen, Hans-Hellmut Nagel
    Place of PublicationGermany
    PublisherSpringer-Verlag
    Pages221-246
    Number of pages26
    ISBN (Print)9783540339717
    Publication statusPublished - 1 Dec 2006

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume3948 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

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  • Cite this

    Cohn, A. G., Hogg, D. C., Bennett, B., Devin, V., Galata, A., Magee, D. R., Needham, C., & Santos, P. (2006). Cognitive vision: Integrating symbolic qualitative representations with computer vision. In H. Christensen, & H-H. Nagel (Eds.), Cognitive Vision Systems: Sampling the Spectrum of Approaches (pp. 221-246). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 3948 LNCS). Springer-Verlag.