Facial expression classification on web images

Matthias Richter*, Tobias Gehrig, Hazim Kemal Ekenel

*Corresponding author for this work

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

7 Citations (Scopus)

Abstract

In this paper, we present a novel database which, is obtained from the web. It contains 4761 manually labeled images of seven basic expressions performed by a large number of subjects of different gender, age and ethnicity. Furthermore, we develop feature descriptors based on the discrete cosine transform (DCT), local binary patterns (LBP), and Gabor filters, which share a uniform formulation in terms of regions around key points. We explore several strategies to find an optimal selection of these key points. The system achieves 86.2%, 85.9% and 84.4% accuracy on the web image database using the Gabor, LBP, and DCT descriptors, respectively.

Original languageEnglish
Title of host publicationICPR 2012 - 21st International Conference on Pattern Recognition
Pages3517-3520
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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