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    Robust 3D face landmark localization based on local coordinate coding

    Song, M. and Tao, D. and Sun, S. and Chen, C. and Maybank, Stephen J. (2014) Robust 3D face landmark localization based on local coordinate coding. IEEE Transactions on Image Processing 23 (12), pp. 5108-5122. ISSN 1057-7149.

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    Abstract

    In the 3D facial animation and synthesis community, input faces are usually required to be labeled by a set of landmarks for parameterization. Because of the variations in pose, expression and resolution, automatic 3D face landmark localization remains a challenge. In this paper, a novel landmark localization approach is presented. The approach is based on local coordinate coding (LCC) and consists of two stages. In the first stage, we perform nose detection, relying on the fact that the nose shape is usually invariant under the variations in the pose, expression, and resolution. Then, we use the iterative closest points algorithm to find a 3D affine transformation that aligns the input face to a reference face. In the second stage, we perform resampling to build correspondences between the input 3D face and the training faces. Then, an LCC-based localization algorithm is proposed to obtain the positions of the landmarks in the input face. Experimental results show that the proposed method is comparable to state of the art methods in terms of its robustness, flexibility, and accuracy.

    Metadata

    Item Type: Article
    Additional Information: (c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Administrator
    Date Deposited: 03 Nov 2015 15:47
    Last Modified: 28 Jul 2019 01:42
    URI: http://eprints.bbk.ac.uk/id/eprint/13324

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