Robust discriminative response map fitting with constrained local models

Akshay Asthana, Ashish Asthana, Stefanos Zafeiriou, Shiyang Cheng, Maja Pantic

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

    409 Citations (Scopus)
    105 Downloads (Pure)

    Abstract

    We present a novel discriminative regression based approach for the Constrained Local Models (CLMs) framework, referred to as the Discriminative Response Map Fitting (DRMF) method, which shows impressive performance in the generic face fitting scenario. The motivation behind this approach is that, unlike the holistic texture based features used in the discriminative AAM approaches, the response map can be represented by a small set of parameters and these parameters can be very efficiently used for reconstructing unseen response maps. Furthermore, we show that by adopting very simple off-the-shelf regression techniques, it is possible to learn robust functions from response maps to the shape parameters updates. The experiments, conducted on Multi-PIE, XM2VTS and LFPW database, show that the proposed DRMF method outperforms state-of-the-art algorithms for the task of generic face fitting. Moreover, the DRMF method is computationally very efficient and is real-time capable. The current MATLAB implementation takes 1 second per image. To facilitate future comparisons, we release the MATLAB code and the pre-trained models for research purposes.
    Original languageUndefined
    Title of host publicationProceedings of IEEE International Conference on Computer Vision and Pattern Recognition, CVPR 2013
    Place of PublicationUSA
    PublisherIEEE Computer Society
    Pages3444-3451
    Number of pages8
    ISBN (Print)978-0-7695-4989-7
    DOIs
    Publication statusPublished - Jun 2013
    Event26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013 - Portland, OR, USA, Portland, United States
    Duration: 23 Jun 201328 Jun 2013
    Conference number: 26

    Publication series

    NameIEEE Conference on Computer Vision and Pattern Recognition
    PublisherIEEE Computer Society
    ISSN (Print)1063-6919

    Conference

    Conference26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2013
    Abbreviated titleCVPR 2013
    CountryUnited States
    CityPortland
    Period23/06/1328/06/13
    Other23-28 June 2013

    Keywords

    • EWI-24262
    • METIS-302620
    • IR-89534
    • HMI-HF: Human Factors

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