Multi-view facial expression recognition analysis with generic sparse coding feature

Usman Tariq; Jianchao Yang; Thomas S. Huang

doi:10.1007/978-3-642-33885-4_58

Multi-view facial expression recognition analysis with generic sparse coding feature

Usman Tariq, Jianchao Yang, Thomas S. Huang

Coordinated Science Lab

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

Abstract

Expression recognition from non-frontal faces is a challenging research area with growing interest. This paper works with a generic sparse coding feature, inspired from object recognition, for multi-view facial expression recognition. Our extensive experiments on face images with seven pan angles and five tilt angles, rendered from the BU-3DFE database, achieve state-of-the-art results. We achieve a recognition rate of 69.1% on all images with four expression intensity levels, and a recognition performance of 76.1% on images with the strongest expression intensity. We then also present detailed analysis of the variations in expression recognition performance for various pose changes.

Original language	English (US)
Title of host publication	Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
Publisher	Springer
Pages	578-588
Number of pages	11
Edition	PART 3
ISBN (Print)	9783642338847
DOIs	https://doi.org/10.1007/978-3-642-33885-4_58
State	Published - 2012
Event	Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings - Florence, Italy Duration: Oct 7 2012 → Oct 13 2012

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 3
Volume	7585 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings
Country/Territory	Italy
City	Florence
Period	10/7/12 → 10/13/12

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Online availability

10.1007/978-3-642-33885-4_58

Library availability

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Cite this

Tariq, U., Yang, J., & Huang, T. S. (2012). Multi-view facial expression recognition analysis with generic sparse coding feature. In Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings (PART 3 ed., pp. 578-588). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7585 LNCS, No. PART 3). Springer. https://doi.org/10.1007/978-3-642-33885-4_58

Multi-view facial expression recognition analysis with generic sparse coding feature. / Tariq, Usman; Yang, Jianchao; Huang, Thomas S.
Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings. PART 3. ed. Springer, 2012. p. 578-588 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7585 LNCS, No. PART 3).

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

Tariq, U, Yang, J & Huang, TS 2012, Multi-view facial expression recognition analysis with generic sparse coding feature. in Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings. PART 3 edn, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 3, vol. 7585 LNCS, Springer, pp. 578-588, Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings, Florence, Italy, 10/7/12. https://doi.org/10.1007/978-3-642-33885-4_58

Tariq U, Yang J, Huang TS. Multi-view facial expression recognition analysis with generic sparse coding feature. In Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings. PART 3 ed. Springer. 2012. p. 578-588. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3). doi: 10.1007/978-3-642-33885-4_58

Tariq, Usman ; Yang, Jianchao ; Huang, Thomas S. / Multi-view facial expression recognition analysis with generic sparse coding feature. Computer Vision, ECCV 2012 - Workshops and Demonstrations, Proceedings. PART 3. ed. Springer, 2012. pp. 578-588 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 3).

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Multi-view facial expression recognition analysis with generic sparse coding feature

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