ACS'10 Proceedings of the 10th WSEAS international conference on Applied computer science
| Hi-index | 0.00 |
For facial expression recognition, we selected three images: (i) just before speaking, (ii) speaking the first vowel, and (iii) speaking the last vowel in an utterance. In this study, as a pre-processing module, we added a judgment function to distinguish a front-view face for facial expression recognition. A frame of the front-view face in a dynamic image is selected by estimating the face direction. The judgment function measures four feature parameters using thermal image processing, and selects the thermal images that have all the values of the feature parameters within limited ranges which were decided on the basis of training thermal images of front-view faces. As an initial investigation, we adopted the utterance of the Japanese name "Taro," which is semantically neutral. The mean judgment accuracy of the front-view face was 99.5% for six subjects who changed their face direction freely. Using the proposed method, the facial expressions of six subjects were distinguishable with 84.0% accuracy when they exhibited one of the intentional facial expressions of "angry," "happy," "neutral," "sad," and "surprised." We expect the proposed method to be applicable for recognizing facial expressions in daily conversation.