NDLI: Bimodal information analysis for emotion recognition

Content Provider	IEEE Xplore Digital Library
Author	Meghjani, M. Ferrie, F. Dudek, G.
Copyright Year	2009
Description	Author affiliation: McGill University, Department of Electrical and Computer Engineering, Canada (Meghjani, M.; Ferrie, F.) \|\| McGill University, School of Computer Science, Canada (Dudek, G.)
Abstract	We present a bimodal information analysis system for automatic emotion recognition. Our approach is based on the analysis of video sequences which combines facial expressions observed visually with acoustic features to automatically recognize five universal emotion classes: Anger, Disgust, Happiness, Sadness and Surprise. We address the challenges posed during the temporal analysis of the bimodal data and introduce a novel technique for combining the best features of instantaneous and temporal based visual recognition systems. We obtain robust appearance-based visual features which we classify instantaneously and aggregate it temporally to improve the recognition rates when compared to single-frame based instantaneous classification. The performance of the system is further boosted by using the complementary audio information for the bimodal emotion recognition. We combine the two modalities at both feature and score level to compare the respective joint emotion recognition rates. The emotions are instantaneously classified using a Support Vector Machine and sequentially aggregated based on their classification probabilities. This approach is validated on a posed audio-visual database and a natural interactive database. The experiments performed on these databases provide encouraging results with the best combined recognition rate being 82%.
Starting Page	1
Ending Page	6
File Size	246600
Page Count	6
File Format	PDF
ISBN	9781424454976
ISSN	15505790
e-ISBN	9781424454983
DOI	10.1109/WACV.2009.5403035
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Information analysis Emotion recognition Spatial databases Audio databases Video sequences Face recognition Robustness Aggregates Support vector machines Support vector machine classification
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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