Top-view people detection based on multiple subarea pose models for smart home system

Han Wang, Dubok Park, David K. Han, Hanseok Ko

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

    3 Citations (Scopus)

    Abstract

    In this paper, an effective top-view people detection algorithm based on multiple subarea models is proposed for smart home system. Conventional single model based detector is difficult to achieve high performance in top-view people detection since there are too many possible individual poses in the top-view based image scene and it is impossible to cover all the poses with single model. Therefore, this paper develops a model of 9 typical poses to mitigate the low detection performance problem of conventional method. Moreover, by restricting the local scope of every pose model, the proposed approach yields an improved detection rate while reducing false alarm compared to the conventional single model based detector.

    Original languageEnglish
    Title of host publication2016 IEEE International Conference on Consumer Electronics, ICCE 2016
    EditorsFrancisco J. Bellido, Daniel Diaz-Sanchez, Nicholas C. H. Vun, Carsten Dolar, Wing-Kuen Ling
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1-2
    Number of pages2
    ISBN (Electronic)9781467383646
    DOIs
    Publication statusPublished - 2016 Mar 10
    EventIEEE International Conference on Consumer Electronics, ICCE 2016 - Las Vegas, United States
    Duration: 2016 Jan 72016 Jan 11

    Publication series

    Name2016 IEEE International Conference on Consumer Electronics, ICCE 2016

    Other

    OtherIEEE International Conference on Consumer Electronics, ICCE 2016
    Country/TerritoryUnited States
    CityLas Vegas
    Period16/1/716/1/11

    Bibliographical note

    Publisher Copyright:
    © 2016 IEEE.

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Electrical and Electronic Engineering

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