A computational model that enables global amodal completion based on V4 neurons

Kazuhiro Sakamoto, Taichi Kumada, Masafumi Yano

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

    2 Citations (Scopus)

    Abstract

    In natural scenes, objects are often partially occluded. Nonetheless, our visual system can readily complete an object shape from available information and perceive it as a whole, a process known as amodal completion. Although implementation of this completion process is an important issue, visual computation for completion, based on both the local continuity of contours and on global regularities, such as symmetry, has received little attention. Here, we show a novel neurocomputational model based on recent physiological findings, in particular those in visual area V4. The model enables amodal completion through the evaluation of a global constellation of features describing a shapefs contours.

    Original languageEnglish
    Title of host publicationNeural Information Processing
    Subtitle of host publicationTheory and Algorithms - 17th International Conference, ICONIP 2010, Proceedings
    Pages9-16
    Number of pages8
    EditionPART 1
    DOIs
    Publication statusPublished - 2010 Dec 21
    Event17th International Conference on Neural Information Processing, ICONIP 2010 - Sydney, NSW, Australia
    Duration: 2010 Nov 222010 Nov 25

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 1
    Volume6443 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other17th International Conference on Neural Information Processing, ICONIP 2010
    CountryAustralia
    CitySydney, NSW
    Period10/11/2210/11/25

    Keywords

    • amodal completion
    • area V4
    • occluded shape
    • symmetry

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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  • Cite this

    Sakamoto, K., Kumada, T., & Yano, M. (2010). A computational model that enables global amodal completion based on V4 neurons. In Neural Information Processing: Theory and Algorithms - 17th International Conference, ICONIP 2010, Proceedings (PART 1 ed., pp. 9-16). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6443 LNCS, No. PART 1). https://doi.org/10.1007/978-3-642-17537-4_2