Please use this identifier to cite or link to this item:
http://hdl.handle.net/2080/2116| Title: | Robust Facial Expression Recognition using Gabor Feature and Bayesian Discriminating Classifier |
| Authors: | Piparsaniyan, Yamini Sharma, V K Mahapatra, K K |
| Keywords: | Bayesian classification Computer vision Emotion recognition Gabor features PCA |
| Issue Date: | Apr-2014 |
| Citation: | IEEE International Conference on Communicatoin & SIgnal Processing ICCSP 2014, 3rd-5th April 2014, Adhiparashakti Engineering College, Melmaruvathur, Tamilnadu. |
| Abstract: | Automatic facial expression recognition is important for effective Human computer interaction (HCI) as well as autistic children for communication. In this paper, we propose emotion recognition using Gabor feature and simple Bayesian discriminating classifier based on principal component analysis (PCA) for emotion recognition. The multi class classification strategic has been applied based on highest value of log likelihood after training different emotions class. Facial expression images from JAFFE database have been used for training as well as testing. Very high accuracy (96.73 %) of emotion recognition has been obtained with proposed method |
| Description: | Copyright belongs to the Proceeding of Publisher |
| URI: | http://hdl.handle.net/2080/2116 |
| Appears in Collections: | Conference Papers |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| PID3125113.pdf | 293.32 kB | Adobe PDF | View/Open |
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