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31 December 2008 Pose-variant facial expression recognition using an embedded image system
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Proceedings Volume 7130, Fourth International Symposium on Precision Mechanical Measurements; 71300X (2008) https://doi.org/10.1117/12.819570
Event: Fourth International Symposium on Precision Mechanical Measurements, 2008, Anhui, China
Abstract
In recent years, one of the most attractive research areas in human-robot interaction is automated facial expression recognition. Through recognizing the facial expression, a pet robot can interact with human in a more natural manner. In this study, we focus on the facial pose-variant problem. A novel method is proposed in this paper to recognize pose-variant facial expressions. After locating the face position in an image frame, the active appearance model (AAM) is applied to track facial features. Fourteen feature points are extracted to represent the variation of facial expressions. The distance between feature points are defined as the feature values. These feature values are sent to a support vector machine (SVM) for facial expression determination. The pose-variant facial expression is classified into happiness, neutral, sadness, surprise or anger. Furthermore, in order to evaluate the performance for practical applications, this study also built a low resolution database (160x120 pixels) using a CMOS image sensor. Experimental results show that the recognition rate is 84% with the self-built database.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kai-Tai Song, Meng-Ju Han, and Shuo-Hung Chang "Pose-variant facial expression recognition using an embedded image system", Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71300X (31 December 2008); https://doi.org/10.1117/12.819570
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