Improved 3D model search for facial feature location and pose estimation in 2D images

Angela Caunce, Chris Taylor, Tim Cootes

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

    Abstract

    This paper tackles the problem of accurately matching a 3D deformable face model to sequences of images in challenging real-world scenarios with large amounts of head movement, occlusion, and difficult lighting conditions. A baseline system involves searching with a set of view-dependent local patches to locate image features, and using these to update the face shape model parameters. We show here two modifications that lead to improvements in performance and can be applied in other similar systems. These are: explicitly searching for occluding boundaries, which prevents the model from rotating rather than changing shape; and a simple method for weighting the relative importance of each located match for model fit. We demonstrate the improvements on both standard test sets and on a series of difficult in-car driver videos, showing more accurate matching and fewer search failures. © 2010. The copyright of this document resides with its authors.
    Original languageEnglish
    Title of host publicationBritish Machine Vision Conference, BMVC 2010 - Proceedings|Br. Mach. Vis. Conf., BMVC - Proc.
    PublisherBMVA Press
    Number of pages1
    DOIs
    Publication statusPublished - 2010
    Event2010 21st British Machine Vision Conference, BMVC 2010 - Aberystwyth
    Duration: 1 Jul 2010 → …

    Conference

    Conference2010 21st British Machine Vision Conference, BMVC 2010
    CityAberystwyth
    Period1/07/10 → …

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