Commonsense knowledge-based face detection

A. Z. Kouzani, F. He, K. Sammut

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    14 Citations (Scopus)

    Abstract

    A connectionist model is presented for commonsense knowledge representation and reasoning. The representation and reasoning ability of the model is described through examples. The commonsense knowledge base is employed to develop a human face detection system. The system consists of three stages: preprocessing, face-components extraction, and final decision-making. A neural network-based algorithm is utilized to extract face components. Five networks are trained to detect mouth, nose, eyes, and full face. The detected face components and their corresponding possibility degrees allow the knowledge base to locate faces in the image and generate a membership degree for the detected faces within the face class. The experimental results obtained using this method are presented.

    Original languageEnglish
    Title of host publicationProceedings of IEEE International Conference on Intelligent Engineering Systems
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages215-220
    Number of pages6
    ISBN (Print)0-7803-3627-5
    DOIs
    Publication statusPublished - 1997
    EventProceedings of the 1997 International Conference on Intelligent Engineering Systems, INES - Budapest, Hungary
    Duration: 15 Sep 199717 Sep 1997

    Conference

    ConferenceProceedings of the 1997 International Conference on Intelligent Engineering Systems, INES
    CityBudapest, Hungary
    Period15/09/9717/09/97

    Fingerprint

    Dive into the research topics of 'Commonsense knowledge-based face detection'. Together they form a unique fingerprint.

    Cite this