University of Surrey

Test tubes in the lab Research in the ATI Dance Research

Audio-visual feature selection and reduction for emotion classification

Haq, S, Jackson, PJB and Edge, J (2008) Audio-visual feature selection and reduction for emotion classification

Available under License : See the attached licence file.

Download (307kB)
[img] Text (licence)

Download (1kB)


Recognition of expressed emotion from speech and facial gestures was investigated in experiments on an audio-visual emotional database. A total of 106 audio and 240 visual features were extracted and then features were selected with Plus l-Take Away r algorithm based on Bhattacharyya distance criterion. In the second step, linear transformation methods, principal component analysis (PCA) and linear discriminant analysis (LDA), were applied to the selected features and Gaussian classifiers were used for classification of emotions. The performance was higher for LDA features compared to PCA features. The visual features performed better than audio features, for both PCA and LDA. Across a range of fusion schemes, the audio-visual feature results were close to that of visual features. A highest recognition rate of 53% was achieved with audio features, 98% with visual features, and 98% with audio-visual features selected by Bhattacharyya distance and transformed by LDA.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing
Authors :
Haq, S
Jackson, PJB
Edge, J
Date : September 2008
Additional Information : Copyright 2008 ISCA
Depositing User : Symplectic Elements
Date Deposited : 21 Mar 2012 12:57
Last Modified : 31 Oct 2017 14:12

Actions (login required)

View Item View Item


Downloads per month over past year

Information about this web site

© The University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
+44 (0)1483 300800