3d Facial Tracking From Corrupted Movie Sequences

dc.creatorGoldenstein S.
dc.creatorVogler C.
dc.creatorMetaxas D.
dc.date2004
dc.date2015-06-26T14:24:27Z
dc.date2015-11-26T14:13:34Z
dc.date2015-06-26T14:24:27Z
dc.date2015-11-26T14:13:34Z
dc.date.accessioned2018-03-28T21:14:20Z
dc.date.available2018-03-28T21:14:20Z
dc.identifier
dc.identifierProceedings Of The Ieee Computer Society Conference On Computer Vision And Pattern Recognition. , v. 1, n. , p. I880 - I885, 2004.
dc.identifier10636919
dc.identifier
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-5044222276&partnerID=40&md5=fbeaec17a38f1da8438b519e645cc554
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/94462
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/94462
dc.identifier2-s2.0-5044222276
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1242316
dc.descriptionIn this paper we perform 3D face tracking on corrupted video sequences. We use a deformable model, combined with a predictive filter, to recover both the rigid transformations and the values of the parameters that describe the evolution of the facial expressions over time. To be robust, predictive filters need a good observation of the system's state. We describe a new method to measure, at each moment in time, the correct distribution of an observation of the parameters of a high-dimensional deformable model. This method is based on bounding the confidence regions of the 2D image displacements with affine forms, and propagating them into parameter space. Using Lindeberg's theorem, we measure a good Gaussian approximation of the parameters in a manner that avoids many of the traditional assumptions about the observations' distributions. We demonstrate in experiments on sequences with compression artifacts, and poor-quality video sequences of Lauren Bacall and Humphrey Bogart from the 1950s, that, without any learning involved, our method is sufficiently robust to extract information from degraded image sequences. In addition, we provide ground truth validation.
dc.description1
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dc.descriptionI880
dc.descriptionI885
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dc.languageen
dc.publisher
dc.relationProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
dc.rightsfechado
dc.sourceScopus
dc.title3d Facial Tracking From Corrupted Movie Sequences
dc.typeActas de congresos


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