Facial Expression Recognition by Using Artificial Neural Network and Fuzzy Inference Applied In Intelligent Household Appliance

• Main Authors: Hung-Ta Shen, 沈宏達
• Other Authors: 駱榮欽
• Format: Others
• Language: en_US
• Published: 2005
• Online Access: http://ndltd.ncl.edu.tw/handle/y749vv

碩士 === 國立臺北科技大學 === 機電整合研究所 === 93 === Automatic facial expression recognition applied in the intelligent household appliance system is a very important step. On this subject, most researchers attempt to recognize prototypic emotional expression. Although humans seem to recognize facial expression in cluttered scenes with relative ease, machine recognition in real-time is always a much more complex task. The major difficult issue is how to segment and extract human facial features precisely and then to recognize facial expression from these features. In the study, we also develop an intelligent household appliance system which can detect and recognize human facial expression. We propose an improved color active contour model (ICACM) that use color information in RGB color space from local facial organ to extract facial features. The features include the contours of eyes, eyebrows and mouth. To increase stability of the contour outline, we applied external energy named valley energy. From several experimental results, the method of facial feature extraction we proposed is more accurate than the original active contour model. The algorithm comprises five steps: First, discriminate skin color from background in RGB color space; second, search the candidates of the face region and fit in with best-fit ellipse; third, locate facial feature and set initial position of contour; fourth, use modified active contour model to extract facial features and feature points from the face candidate; fifth, recognize human facial expression by neural network and fuzzy decision system.