Reinforcement learning in computer vision

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    6 Citations (Scopus)


    Nowadays, machine learning has become one of the basic technologies used in solving various computer vision tasks such as feature detection, image segmentation, object recognition and tracking. In many applications, various complex systems such as robots are equipped with visual sensors from which they learn state of surrounding environment by solving corresponding computer vision tasks. Solutions of these tasks are used for making decisions about possible future actions. It is not surprising that when solving computer vision tasks we should take into account special aspects of their subsequent application in model-based predictive control. Reinforcement learning is one of modern machine learning technologies in which learning is carried out through interaction with the environment. In recent years, Reinforcement learning has been used both for solving such applied tasks as processing and analysis of visual information, and for solving specific computer vision problems such as filtering, extracting image features, localizing objects in scenes, and many others. The paper describes shortly the Reinforcement learning technology and its use for solving computer vision problems.

    Original languageEnglish
    Title of host publicationTenth International Conference on Machine Vision, ICMV 2017
    EditorsJianhong Zhou, Antanas Verikas, Dmitry Nikolaev, Petia Radeva
    ISBN (Electronic)9781510619418
    Publication statusPublished - 2018
    Event10th International Conference on Machine Vision, ICMV 2017 - Vienna, Austria
    Duration: 13 Nov 201715 Nov 2017

    Publication series

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


    Conference10th International Conference on Machine Vision, ICMV 2017


    • Computer vision
    • reinforcement learning


    Dive into the research topics of 'Reinforcement learning in computer vision'. Together they form a unique fingerprint.

    Cite this