- Volume 15 Issue 1
DOI QR Code
Comparison of Computer and Human Face Recognition According to Facial Components
- Nam, Hyun-Ha (Department of Computer Science, Graduate School of Information Science and Engineering, Tokyo Institute of Technology) ;
- Kang, Byung-Jun (Technical Research Institute, Hyundai Mobis) ;
- Park, Kang-Ryoung (Division of Electronics and Electrical Engineering, Dongguk University)
- Received : 2011.09.19
- Accepted : 2011.11.22
- Published : 2012.01.31
Face recognition is a biometric technology used to identify individuals based on facial feature information. Previous studies of face recognition used features including the eye, mouth and nose; however, there have been few studies on the effects of using other facial components, such as the eyebrows and chin, on recognition performance. We measured the recognition accuracy affected by these facial components, and compared the differences between computer-based and human-based facial recognition methods. This research is novel in the following four ways compared to previous works. First, we measured the effect of components such as the eyebrows and chin. And the accuracy of computer-based face recognition was compared to human-based face recognition according to facial components. Second, for computer-based recognition, facial components were automatically detected using the Adaboost algorithm and active appearance model (AAM), and user authentication was achieved with the face recognition algorithm based on principal component analysis (PCA). Third, we experimentally proved that the number of facial features (when including eyebrows, eye, nose, mouth, and chin) had a greater impact on the accuracy of human-based face recognition, but consistent inclusion of some feature such as chin area had more influence on the accuracy of computer-based face recognition because a computer uses the pixel values of facial images in classifying faces. Fourth, we experimentally proved that the eyebrow feature enhanced the accuracy of computer-based face recognition. However, the problem of occlusion by hair should be solved in order to use the eyebrow feature for face recognition.
Supported by : Korea Research Council of Fundamental Science & Technology
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