Machine vision and appearance based learning

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    1 Citation (Scopus)

    Abstract

    Smart algorithms are used in Machine vision to organize or extract high-level information from the available data. The resulted high-level understanding the content of images received from certain visual sensing system and belonged to an appearance space can be only a key first step in solving various specific tasks such as mobile robot navigation in uncertain environments, road detection in autonomous driving systems, etc. Appearance-based learning has become very popular in the field of machine vision. In general, the appearance of a scene is a function of the scene content, the lighting conditions, and the camera position. Mobile robots localization problem in machine learning framework via appearance space analysis is considered. This problem is reduced to certain regression on an appearance manifold problem, and newly regression on manifolds methods are used for its solution.

    Original languageEnglish
    Title of host publicationNinth International Conference on Machine Vision, ICMV 2016
    EditorsDmitry P. Nikolaev, Antanas Verikas, Jianhong Zhou, Petia Radeva, Wei Zhang
    PublisherSPIE
    Volume10341
    ISBN (Electronic)9781510611313
    DOIs
    Publication statusPublished - 2017
    Event9th International Conference on Machine Vision, ICMV 2016 - Nice, France
    Duration: 18 Nov 201620 Nov 2016

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume10341
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Conference

    Conference9th International Conference on Machine Vision, ICMV 2016
    Country/TerritoryFrance
    CityNice
    Period18/11/1620/11/16

    Keywords

    • appearance space
    • Machine vision
    • manifold learning
    • regression on appearance manifold
    • robot localization

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