A robust face detector algorithm utilizing neural networks and partial template matching

Pitoyo Hartono*, Shuji Hashimoto

*Corresponding author for this work

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

    2 Citations (Scopus)


    Face detection from an arbitrary scene has become a very actively studied topic in the image processing and pattern recognition fields. The reason for the importance of face detection is in its broad applications, for example in human detection by means of visual input for security reason, human-machine interaction, and video archiving. Human face is composed from several components, each with large varieties and it can take many postures in arbitrary scene, which make detection task a very difficult one. In this study we propose a method for robust face detection from arbitrary scene utilizing neural network as face's posture predictor and partial template matching of human face. The proposed model is robust to the lighting conditions and postures of the frontal faces.

    Original languageEnglish
    Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
    EditorsS. Kaneko, H. Cho, G.K. Knopf, R. Tutsch
    Number of pages9
    Publication statusPublished - 2004
    EventMachine Vision and its Optomechatronic Applications - Philadelphia, PA, United States
    Duration: 2004 Oct 262004 Oct 28


    OtherMachine Vision and its Optomechatronic Applications
    Country/TerritoryUnited States
    CityPhiladelphia, PA


    • Face Detection
    • Neural Network
    • Template Matching
    • Voting

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering
    • Condensed Matter Physics


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