Human detection using gradient maps and golden ratio

Feng Su, Gu Fang

    Research output: Chapter in Book / Conference PaperConference Paperpeer-review

    1 Citation (Scopus)

    Abstract

    ![CDATA[Human detection is an important topic that can be used for many applications, it is mainly found in areas that required surveillance such as airports, casinos, factories, construction and mining sites. In this paper, a novel human detection method is introduced to extract the human figure from an input image without prior information or training. This method firstly uses a head and shoulder detection scheme based on curve detection with scaled gradient magnitude and orientation maps. It is then followed by a human body estimation scheme based on gap detection and golden ratio. Finally, the human figure is extracted through thresholding local gradient magnitude regions and horizontal filling. Tests on various images have shown that this method is capable of detecting and extracting human body figures robustly from different images.]]
    Original languageEnglish
    Title of host publicationProceedings of the 31st International Symposium on Automation and Robotics in Construction and Mining (ISARC 2014), 9-11 July 2014, Sydney, Australia
    PublisherUniversity of Technology Sydney
    Pages890-896
    Number of pages7
    ISBN (Print)9780646597119
    Publication statusPublished - 2014
    EventInternational Symposium on Automation and Robotics in Construction -
    Duration: 9 Jul 2014 → …

    Conference

    ConferenceInternational Symposium on Automation and Robotics in Construction
    Period9/07/14 → …

    Keywords

    • Data mining
    • Image processing
    • Optical pattern recognition
    • Robotics
    • Security measures

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