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Publication Type : Conference Proceedings
Publisher : First International Symposium on Signal Processing and Intelligent Recognition Systems - SIRS 2014
Source : First International Symposium on Signal Processing and Intelligent Recognition Systems - SIRS 2014, Springer, IIITMK- Technopark, Trivandrum, India (2014)
Url : https://link.springer.com/chapter/10.1007/978-3-319-04960-1_27
ISBN : 9783319049601
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2014
Abstract : An emotion recognition system from facial expression is used for recognizing expressions from the facial images and classifying them into one of the six basic emotions. Feature extraction and classification are the two main steps in an emotion recognition system. In this paper, two approaches viz., cropped face and whole face methods for feature extraction are implemented separately on the images taken from Cohn-Kanade (CK) and JAFFE database. Transform techniques such as Dual – Tree Complex Wavelet Transform (DT-CWT) and Gabor Wavelet Transform are considered for the formation of feature vectors along with Neural Network (NN) and K-Nearest Neighbor (KNN) as the Classifiers. These methods are combined in different possible combinations with the two aforesaid approaches and the databases to explore their efficiency. The overall average accuracy is 93{%} and 80{%} for NN and KNN respectively. The results are compared with those existing in literature and prove to be more efficient. The results suggest that cropped face approach gives better results compared to whole face approach. DT-CWT outperforms Gabor wavelet technique for both classifiers.
Cite this Research Publication : Dr. Suja P., Tripathi, S., and Deepthy, J., “Emotion Recognition From Facial Expressions Using Frequency Domain Techniques”, in First International Symposium on Signal Processing and Intelligent Recognition Systems - SIRS 2014, IIITMK- Technopark, Trivandrum, India, 2014.