Abstract—This paper concerns the automatic recognition of human facial expressions using a fast 3D sensor, such as the Kinect. Facial expressions represent a rich source of information regarding emotion and interpersonal communication. The ability to recognize expressions automatically will have a large impact in many areas, particularly human-computer interaction. This paper describes 2 frameworks for recognizing 6 basic expressions using 3-dimensional data sequences that are captured in real time. Results are presented that demonstrate accuracy levels for the different techniques, and for different methods of preprocessing, registration and classification. We also describe the potential to use such a system for treatment of children with autism spectrum disorders (ASD).
Index Terms—Kinect, SVM, Emotion, ASD
The authors are with the Bradley Department of Electrical and Computer Engineering, Virginia Tech, Blacksburg, USA, on leave from Scientific Research and Technology Applications City, Alexandria, Egypt (e-mail: amira@vt.edu, sherin@vt.edu, nady@vt.edu, abbott@vt.edu).
[PDF]
Cite:Amira E. Youssef, Sherin F. Aly, Ahmed S. Ibrahim, and A. Lynn Abbott, "Auto-Optimized Multimodal Expression Recognition Framework Using 3D Kinect Data for ASD Therapeutic Aid," International Journal of Modeling and Optimization vol. 3, no. 2, pp. 112-115, 2013.
![[Click]](http://www.ijmo.org/img/ijmo_v7n5-v8n4_ei%28inspec%29_indexscreenshot.jpg){kind=link}