Recognition of Human Facial Expression in a Video Image using the Active Appearance Model
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Tracking human facial expression within a video image has many useful applications, such as surveillance and teleconferencing, etc. Initially, the Active Appearance Model (AAM) was proposed for facial recognition; however, it turns out that the AAM has many advantages as regards continuous facial expression recognition. We have implemented a continuous facial expression recognition system using the AAM. In this study, we adopt an independent AAM using the Inverse Compositional Image Alignment method. The system was evaluated using the standard Cohn-Kanade facial expression database, the results of which show that it could have numerous potential applications.
Abstract
Tracking human facial expression within a video image has many useful applications, such as surveillance and teleconferencing, etc. Initially, the Active Appearance Model (AAM) was proposed for facial recognition; however, it turns out that the AAM has many advantages as regards continuous facial expression recognition. We have implemented a continuous facial expression recognition system using the AAM. In this study, we adopt an independent AAM using the Inverse Compositional Image Alignment method. The system was evaluated using the standard Cohn-Kanade facial expression database, the results of which show that it could have numerous potential applications.
참고문헌 (3)
- Matthews, I, "Active Appearance Models Revisited", International Journal of Computer Vision, pp.135~164 (2004)
- Edwards, G.J, "Interpreting Face Images using Active Appearance Models", Proc. of the International Conference on Automatic Face and Gesture Recognition, pp.300~305 (1998), June
- Lucas, B, "An iterative image registration technique and its application to stereo vision", Proc. of the International Joint Conference on Artificial Intelligence, pp.674~679 (1981)