Feature selection for 2D and 3D face recognition

    Research output: Chapter in Book/Conference paperEntry for encyclopedia/dictionary

    Abstract

    Face recognition is a popular research topic with a number of applications in several industrial sectors including security, surveillance, entertainment, virtual reality, and human–machine interaction. Both 2D images and 3D data can now be easily acquired and used for face recognition. For any 2D/3D face recognition system, feature extraction and selection play a significant role. Currently, both holistic and local features have been intensively investigated in the literature. In this article, fundamental background knowledge of face recognition, including 2D/3D data acquisition, data preprocessing, feature extraction, classification, and performance evaluation, is presented. The state-of-the-art feature extraction algorithms, including 2D holistic feature, 2D local feature, 3D holistic feature, and 3D local feature extraction algorithms, are then described in detail. Finally, feature selection and fusion techniques are presented. The article covers the complete related aspects of feature selection for 2D and 3D face recognition.

    Original languageEnglish
    Title of host publicationWiley encyclopedia of electrical and electronics engineering
    EditorsBrett Kurzman
    Place of PublicationHoboken, NJ
    PublisherJohn Wiley & Sons
    ISBN (Electronic)9780471346081
    DOIs
    Publication statusPublished - 15 Jun 2015

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    Face recognition
    Feature extraction
    Virtual reality
    Data acquisition
    Fusion reactions

    Cite this

    Bennamoun, M., Guo, Y., & Sohel, F. (2015). Feature selection for 2D and 3D face recognition. In B. Kurzman (Ed.), Wiley encyclopedia of electrical and electronics engineering Hoboken, NJ: John Wiley & Sons. https://doi.org/10.1002/047134608X.W8257
    Bennamoun, Mohammed ; Guo, Yulan ; Sohel, Ferdous. / Feature selection for 2D and 3D face recognition. Wiley encyclopedia of electrical and electronics engineering. editor / Brett Kurzman. Hoboken, NJ : John Wiley & Sons, 2015.
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    abstract = "Face recognition is a popular research topic with a number of applications in several industrial sectors including security, surveillance, entertainment, virtual reality, and human–machine interaction. Both 2D images and 3D data can now be easily acquired and used for face recognition. For any 2D/3D face recognition system, feature extraction and selection play a significant role. Currently, both holistic and local features have been intensively investigated in the literature. In this article, fundamental background knowledge of face recognition, including 2D/3D data acquisition, data preprocessing, feature extraction, classification, and performance evaluation, is presented. The state-of-the-art feature extraction algorithms, including 2D holistic feature, 2D local feature, 3D holistic feature, and 3D local feature extraction algorithms, are then described in detail. Finally, feature selection and fusion techniques are presented. The article covers the complete related aspects of feature selection for 2D and 3D face recognition.",
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    Bennamoun, M, Guo, Y & Sohel, F 2015, Feature selection for 2D and 3D face recognition. in B Kurzman (ed.), Wiley encyclopedia of electrical and electronics engineering. John Wiley & Sons, Hoboken, NJ. https://doi.org/10.1002/047134608X.W8257

    Feature selection for 2D and 3D face recognition. / Bennamoun, Mohammed; Guo, Yulan; Sohel, Ferdous.

    Wiley encyclopedia of electrical and electronics engineering. ed. / Brett Kurzman. Hoboken, NJ : John Wiley & Sons, 2015.

    Research output: Chapter in Book/Conference paperEntry for encyclopedia/dictionary

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    Bennamoun M, Guo Y, Sohel F. Feature selection for 2D and 3D face recognition. In Kurzman B, editor, Wiley encyclopedia of electrical and electronics engineering. Hoboken, NJ: John Wiley & Sons. 2015 https://doi.org/10.1002/047134608X.W8257