Symmetrical judgment and improvement of CoHOG feature descriptor for pedestrian detection

Hirokatsu Kataoka, Yoshimitsu Aoki

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

    2 Citations (Scopus)

    Abstract

    Pedestrian detection method is the highest priority for "active safety" which prevents traffic accidents before happens. In previous studies, edge orientation based feature descriptors are proposed. Recently, high standard detection algorithm, Co-occurrence Histograms of Oriented Gradients (CoHOG) is proposed. However, this method has miss detection in complicated situation and processing cost is high. We propose symmetrical judgment algorithm and an extended version of CoHOG for high speed and high accuracy pedestrian detection. The effectiveness of the proposed method was proved on pedestrian detection performance test.

    Original languageEnglish
    Title of host publicationProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011
    Pages536-539
    Number of pages4
    Publication statusPublished - 2011 Dec 1
    Event12th IAPR Conference on Machine Vision Applications, MVA 2011 - Nara, Japan
    Duration: 2011 Jun 132011 Jun 15

    Publication series

    NameProceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011

    Other

    Other12th IAPR Conference on Machine Vision Applications, MVA 2011
    CountryJapan
    CityNara
    Period11/6/1311/6/15

    ASJC Scopus subject areas

    • Computer Vision and Pattern Recognition

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  • Cite this

    Kataoka, H., & Aoki, Y. (2011). Symmetrical judgment and improvement of CoHOG feature descriptor for pedestrian detection. In Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011 (pp. 536-539). (Proceedings of the 12th IAPR Conference on Machine Vision Applications, MVA 2011).