Towards Large-Scale 3D Face Recognition

    Research output: Chapter in Book/Conference paperConference paper

    1 Citation (Scopus)

    Abstract

    3D face recognition holds great promise in achieving robustness to pose, expressions and occlusions. However, 3D face recognition algorithms are still far behind their 2D counterparts due to the lack of large-scale datasets. We present a model based algorithm for 3D face recognition and test its performance by combining two large public datasets of 3D faces. We propose a Fully Convolutional Deep Network (FCDN) to initialize our algorithm. Reliable seed points are then extracted from each 3D face by evolving level set curves with a single curvature dependent adaptive speed function. We then establish dense correspondence between the faces in the training set by matching the surface around the seed points on a template face to the ones on the target faces. A morphable model is then fitted to probe faces and face recognition is performed by matching the parameters of the probe and gallery faces. Our algorithm achieves state of the art landmark localization results. Face recognition results on the combined FRGCv2 and Bosphorus datasets show that our method is effective in recognizing query faces with real world variations in pose and expression, and with occlusion and missing data despite a huge gallery. Comparing results of individual and combined datasets show that the recognition accuracy drops when the size of the gallery increases.

    Original languageEnglish
    Title of host publication2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
    EditorsA.W. Liew, C. Zhou, Y. Gao, Z. Wang, C. Fookes, B. Lovell , M. Blumenstein
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    ISBN (Electronic)9781509028962
    DOIs
    Publication statusPublished - 22 Dec 2016
    Event2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016: DICTA 2016 - Gold Coast, Australia
    Duration: 30 Nov 20162 Dec 2016

    Conference

    Conference2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016
    CountryAustralia
    CityGold Coast
    Period30/11/162/12/16

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  • Cite this

    Gilani, Z., & Mian, A. (2016). Towards Large-Scale 3D Face Recognition. In A. W. Liew, C. Zhou, Y. Gao, Z. Wang, C. Fookes, B. Lovell , & M. Blumenstein (Eds.), 2016 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2016 [7797090] IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/DICTA.2016.7797090