In this paper, we propose a novel approach for facial expression analysis and recognition. The main contributions of the paper are as follows. First, we propose an efficient facial expression recognition scheme based on the detection of keyframes in videos where the recognition is performed using a temporal classifier. Second, we use the proposed method for extending the human-machine interaction functionality of the AIBO robot. More precisely, the robot is displaying an emotional state in response to the recognized user's facial expression. Experiments using unseen videos demonstrated the effectiveness of the developed method. © Springer-Verlag Berlin Heidelberg 2007.
CITATION STYLE
Dornaika, F., & Raducanu, B. (2007). Efficient facial expression recognition for human robot interaction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4507 LNCS, pp. 700–708). Springer Verlag. https://doi.org/10.1007/978-3-540-73007-1_84
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