University of Oulu

L. Zafeiriou, S. Zafeiriou and M. Pantic, "Deep Analysis of Facial Behavioral Dynamics," 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Honolulu, HI, 2017, pp. 1988-1996. doi: 10.1109/CVPRW.2017.249

Deep analysis of facial behavioral dynamics

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Author: Zafeiriou, Lazaros1,2; Zafeiriou, Stefanos1,3; Pantic, Maja1,4
Organizations: 1Imperial College London, UK
2AimBrain, UK
3Center for Machine Vision and Signal Analysis, University of Oulu, Finland
4University of Twente, The Netherlands
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 2.5 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe202003057309
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2020-03-05
Description:

Abstract

Modelling of facial dynamics, as well as recovering of latent dimensions that correspond to facial dynamics is of paramount importance for many tasks relevant to facial behaviour analysis. Currently, analysis of facial dynamics is performed by applying linear techniques, mainly, on sparse facial tracks. In this, paper we propose the first, to the best of our knowledge, methodology for extracting low-dimensional latent dimensions that correspond to facial dynamics (i.e., motion of facial parts). To this end we develop appropriate unsupervised and supervised deep autoencoder architectures, which are able to extract features that correspond to the facial dynamics. We demonstrate the usefulness of the proposed approach in various facial behaviour datasets.

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Series: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN: 1063-6919
ISSN-L: 1063-6919
ISBN Print: 978-1-5386-0733-6
Pages: 1988 - 1996
DOI: 10.1109/CVPRW.2017.249
OADOI: https://oadoi.org/10.1109/CVPRW.2017.249
Host publication: 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)
Conference: IEEE Conference on Computer Vision and Pattern Recognition Workshops
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
Subjects:
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