Automatic facial expression recognition using features of salient facial patches
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- 29 December 2014
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Affective Computing
- Vol. 6 (1), 1-12
- https://doi.org/10.1109/taffc.2014.2386334
Abstract
Extraction of discriminative features from salient facial patches plays a vital role in effective facial expression recognition. The accurate detection of facial landmarks improves the localization of the salient patches on face images. This paper proposes a novel framework for expression recognition by using appearance features of selected facial patches. A few prominent facial patches, depending on the position of facial landmarks, are extracted which are active during emotion elicitation. These active patches are further processed to obtain the salient patches which contain discriminative features for classification of each pair of expressions, thereby selecting different facial patches as salient for different pair of expression classes. One-against-one classification method is adopted using these features. In addition, an automated learning-free facial landmark detection technique has been proposed, which achieves similar performances as that of other state-of-art landmark detection methods, yet requires significantly less execution time. The proposed method is found to perform well consistently in different resolutions, hence, providing a solution for expression recognition in low resolution images. Experiments on CK+ and JAFFE facial expression databases show the effectiveness of the proposed system.Keywords
This publication has 55 references indexed in Scilit:
- Robust Facial Expression Recognition Based on Local Directional PatternETRI Journal, 2010
- The painful face – Pain expression recognition using active appearance modelsImage and Vision Computing, 2009
- Facial expression recognition based on Local Binary Patterns: A comprehensive studyImage and Vision Computing, 2009
- A comparison of methods for multiclass support vector machinesIEEE Transactions on Neural Networks, 2002
- Multiresolution gray-scale and rotation invariant texture classification with local binary patternsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2002
- Active appearance modelsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2001
- Automatic classification of single facial imagesIEEE Transactions on Pattern Analysis and Machine Intelligence, 1999
- Eigenfaces vs. Fisherfaces: recognition using class specific linear projectionIEEE Transactions on Pattern Analysis and Machine Intelligence, 1997
- Support-vector networksMachine Learning, 1995
- Innate and universal facial expressions: Evidence from developmental and cross-cultural research.Psychological Bulletin, 1994