Group expression intensity estimation in videos via Gaussian Processes

Abhinav Dhall*, Roland Goecke

*Corresponding author for this work

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

    20 Citations (Scopus)

    Abstract

    Facial expression analysis has been a very active field of research in recent years. This paper proposes a method for finding the apex of an expression, e.g. happiness, in a video containing a group of people based on expression intensity estimation. The proposed method is directly applied to video summarisation based on group happiness and timestamps; further, a novel Gaussian Process Regression based expression intensity estimation method is described. To demonstrate its performance, experiments on smile intensity estimation are performed and compared to other regression based techniques. The smile intensity estimator is extended to group happiness intensity estimation. The proposed intensity estimator can be extended easily for other expressions. The experiments are performed on an 'in the wild' dataset. Quantitative results are presented for comparison of our happiness-intensity detector. A user study was also conducted to verify the results of the proposed method.

    Original languageEnglish
    Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
    Pages3525-3528
    Number of pages4
    Publication statusPublished - 2012
    Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
    Duration: 11 Nov 201215 Nov 2012

    Publication series

    NameProceedings - International Conference on Pattern Recognition
    ISSN (Print)1051-4651

    Conference

    Conference21st International Conference on Pattern Recognition, ICPR 2012
    Country/TerritoryJapan
    CityTsukuba
    Period11/11/1215/11/12

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