3D Face Recognition

Ajmal Mian, N. Pears

    Research output: Chapter in Book/Conference paperChapter

    Abstract

    Face recognition using standard 2D images struggles to cope with changes in illumination and pose. 3D face recognition algorithms have been more successful in dealing with these challenges. 3D face shape data is used as an independent cue for face recognition and has also been combined with texture to facilitate multimodal face recognition. Additionally, 3D face models have been used for pose correction and calculation of the facial albedo map, which is invariant to illumination. Finally, 3D face recognition has also achieved significant success towards expression invariance by modeling non-rigid surface deformations, removing facial expressions or by using parts-based face recognition. This chapter gives an overview of 3D face recognition and details both well-established and more recent state-of-the-art 3D face recognition techniques in terms of their implementation and expected performance on benchmark datasets.
    Original languageEnglish
    Title of host publication3D Imaging, Analysis and Applications
    EditorsNick Pears, Yonghuai Liu, Peter Bunting
    Place of PublicationUK
    PublisherSpringer
    Pages311-366
    ISBN (Print)9781447140627
    DOIs
    Publication statusPublished - 2012

    Fingerprint

    Face recognition
    Lighting
    Invariance
    Textures

    Cite this

    Mian, A., & Pears, N. (2012). 3D Face Recognition. In N. Pears, Y. Liu, & P. Bunting (Eds.), 3D Imaging, Analysis and Applications (pp. 311-366). UK: Springer. https://doi.org/10.1007/978-1-4471-4063-4
    Mian, Ajmal ; Pears, N. / 3D Face Recognition. 3D Imaging, Analysis and Applications. editor / Nick Pears ; Yonghuai Liu ; Peter Bunting. UK : Springer, 2012. pp. 311-366
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    abstract = "Face recognition using standard 2D images struggles to cope with changes in illumination and pose. 3D face recognition algorithms have been more successful in dealing with these challenges. 3D face shape data is used as an independent cue for face recognition and has also been combined with texture to facilitate multimodal face recognition. Additionally, 3D face models have been used for pose correction and calculation of the facial albedo map, which is invariant to illumination. Finally, 3D face recognition has also achieved significant success towards expression invariance by modeling non-rigid surface deformations, removing facial expressions or by using parts-based face recognition. This chapter gives an overview of 3D face recognition and details both well-established and more recent state-of-the-art 3D face recognition techniques in terms of their implementation and expected performance on benchmark datasets.",
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    language = "English",
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    editor = "Nick Pears and Yonghuai Liu and Peter Bunting",
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    Mian, A & Pears, N 2012, 3D Face Recognition. in N Pears, Y Liu & P Bunting (eds), 3D Imaging, Analysis and Applications. Springer, UK, pp. 311-366. https://doi.org/10.1007/978-1-4471-4063-4

    3D Face Recognition. / Mian, Ajmal; Pears, N.

    3D Imaging, Analysis and Applications. ed. / Nick Pears; Yonghuai Liu; Peter Bunting. UK : Springer, 2012. p. 311-366.

    Research output: Chapter in Book/Conference paperChapter

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    AU - Pears, N.

    PY - 2012

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    AB - Face recognition using standard 2D images struggles to cope with changes in illumination and pose. 3D face recognition algorithms have been more successful in dealing with these challenges. 3D face shape data is used as an independent cue for face recognition and has also been combined with texture to facilitate multimodal face recognition. Additionally, 3D face models have been used for pose correction and calculation of the facial albedo map, which is invariant to illumination. Finally, 3D face recognition has also achieved significant success towards expression invariance by modeling non-rigid surface deformations, removing facial expressions or by using parts-based face recognition. This chapter gives an overview of 3D face recognition and details both well-established and more recent state-of-the-art 3D face recognition techniques in terms of their implementation and expected performance on benchmark datasets.

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    BT - 3D Imaging, Analysis and Applications

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    A2 - Liu, Yonghuai

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    Mian A, Pears N. 3D Face Recognition. In Pears N, Liu Y, Bunting P, editors, 3D Imaging, Analysis and Applications. UK: Springer. 2012. p. 311-366 https://doi.org/10.1007/978-1-4471-4063-4