PGT: Proposal-guided object tracking

Han Ul Kim, Chang-Su Kim

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

    Abstract

    We propose a robust visual tracking system, which refines initial estimates of a base tracker by employing object proposal techniques. First, we decompose the base tracker into three building blocks: Representation method, appearance model, and model update strategy. We then design each building block by adopting and improving ideas from recent successful trackers. Second, we propose the proposal-guided tracking (PGT) algorithm. Given proposals generated by an edge-based object proposal technique, we select only the proposals that can improve the result of the base tracker using several cues. Then, we discriminate target proposals from non-target ones, based on the nearest neighbor classification using the target and background models. Finally, we replace the result of the base tracker with the best target proposal. Experimental results demonstrate that proposed PGT algorithm provides excellent results on a visual tracking benchmark.

    Original languageEnglish
    Title of host publicationProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1762-1767
    Number of pages6
    ISBN (Electronic)9781538615423
    DOIs
    Publication statusPublished - 2017 Jul 2
    Event9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia
    Duration: 2017 Dec 122017 Dec 15

    Publication series

    NameProceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
    Volume2018-February

    Other

    Other9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
    Country/TerritoryMalaysia
    CityKuala Lumpur
    Period17/12/1217/12/15

    Bibliographical note

    Funding Information:
    This work was supported partly by the National Research Foundation of Korea (NRF) grant funded by the MSIT(Ministry of Science and ICT), Korea, under the ITRC(Information Technology Research Center) support program(IITP-2017-2016-0-00464) supervised by the

    Publisher Copyright:
    © 2017 IEEE.

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Human-Computer Interaction
    • Information Systems
    • Signal Processing

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