
Proceedings Paper
Pose-variant facial expression recognition using an embedded image systemFormat | Member Price | Non-Member Price |
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Paper 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.
Paper Details
Date Published: 31 December 2008
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71300X (31 December 2008); doi: 10.1117/12.819570
Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)
PDF: 6 pages
Proc. SPIE 7130, Fourth International Symposium on Precision Mechanical Measurements, 71300X (31 December 2008); doi: 10.1117/12.819570
Show Author Affiliations
Kai-Tai Song, National Chiao Tung Univ. (Taiwan)
Meng-Ju Han, National Chiao Tung Univ. (Taiwan)
Meng-Ju Han, National Chiao Tung Univ. (Taiwan)
Shuo-Hung Chang, Industrial Technology Research Institute (Taiwan)
Published in SPIE Proceedings Vol. 7130:
Fourth International Symposium on Precision Mechanical Measurements
Yetai Fei; Kuang-Chao Fan; Rongsheng Lu, Editor(s)
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