Emotion recognition from an ensemble of features

Usman Tariq; Kai Hsiang Lin; Zhen Li; Xi Zhou; Zhaowen Wang; Vuong Le; Thomas S. Huang; Xutao Lv; Tony X. Han

doi:10.1109/FG.2011.5771365

Emotion recognition from an ensemble of features

Usman Tariq, Kai Hsiang Lin, Zhen Li, Xi Zhou, Zhaowen Wang, Vuong Le, Thomas S. Huang, Xutao Lv, Tony X. Han

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This work details the authors' efforts to push the baseline of expression recognition performance on a realistic database. Both subject-dependent and subject-independent emotion recognition scenarios are addressed in this work. These two happen frequently in real life settings. The approach towards solving this problem involves face detection, followed by key point identification, then feature generation and then finally classification. An ensemble of features comprising of Hierarchial Gaussianization (HG), Scale Invariant Feature Transform (SIFT) and Optic Flow have been incorporated. In the classification stage we used SVMs. The classification task has been divided into person specific and person independent emotion recognition. Both manual labels and automatic algorithms for person verification have been attempted. They both give similar performance.

Original language	English (US)
Title of host publication	2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
Pages	872-877
Number of pages	6
DOIs	https://doi.org/10.1109/FG.2011.5771365
State	Published - 2011
Externally published	Yes
Event	2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 - Santa Barbara, CA, United States Duration: Mar 21 2011 → Mar 25 2011

Publication series

Name	2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011

Other

Other	2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011
Country/Territory	United States
City	Santa Barbara, CA
Period	3/21/11 → 3/25/11

ASJC Scopus subject areas

Artificial Intelligence
Computer Vision and Pattern Recognition

Online availability

10.1109/FG.2011.5771365

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Tariq, U., Lin, K. H., Li, Z., Zhou, X., Wang, Z., Le, V., Huang, T. S., Lv, X., & Han, T. X. (2011). Emotion recognition from an ensemble of features. In 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 (pp. 872-877). Article 5771365 (2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011). https://doi.org/10.1109/FG.2011.5771365

Emotion recognition from an ensemble of features. / Tariq, Usman; Lin, Kai Hsiang; Li, Zhen et al.
2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011. 2011. p. 872-877 5771365 (2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Tariq, U, Lin, KH, Li, Z, Zhou, X, Wang, Z, Le, V, Huang, TS, Lv, X & Han, TX 2011, Emotion recognition from an ensemble of features. in 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011., 5771365, 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011, pp. 872-877, 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011, Santa Barbara, CA, United States, 3/21/11. https://doi.org/10.1109/FG.2011.5771365

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abstract = "This work details the authors' efforts to push the baseline of expression recognition performance on a realistic database. Both subject-dependent and subject-independent emotion recognition scenarios are addressed in this work. These two happen frequently in real life settings. The approach towards solving this problem involves face detection, followed by key point identification, then feature generation and then finally classification. An ensemble of features comprising of Hierarchial Gaussianization (HG), Scale Invariant Feature Transform (SIFT) and Optic Flow have been incorporated. In the classification stage we used SVMs. The classification task has been divided into person specific and person independent emotion recognition. Both manual labels and automatic algorithms for person verification have been attempted. They both give similar performance.",

author = "Usman Tariq and Lin, {Kai Hsiang} and Zhen Li and Xi Zhou and Zhaowen Wang and Vuong Le and Huang, {Thomas S.} and Xutao Lv and Han, {Tony X.}",

note = "Copyright: Copyright 2011 Elsevier B.V., All rights reserved.; 2011 IEEE International Conference on Automatic Face and Gesture Recognition and Workshops, FG 2011 ; Conference date: 21-03-2011 Through 25-03-2011",

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Emotion recognition from an ensemble of features

Abstract

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ASJC Scopus subject areas

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