Facial expression recognition for human-robot interaction: a prototype
RobVis'08 Proceedings of the 2nd international conference on Robot vision
A new classifier for facial expression recognition: fuzzy buried Markov model
Journal of Computer Science and Technology
A novel real time system for facial expression recognition
ACII'05 Proceedings of the First international conference on Affective Computing and Intelligent Interaction
Real time facial expression recognition using local binary patterns and linear programming
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
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The most expressive way human display emotion is through facial expressions. Facial expression recognition is necessary for designing any practical human-machine interfaces. This paper proposes a novel framework to real-time facial expression recognition within the interactive computer environment. The two major contributions of this work are: First, we proposed a novel network structure and parameters learning algorithm for embedded HMM [1] based on AdaBoost [2]. Second, we apply this optimized embedded HMM to real-time facial expression recognition. In this paper, the embedded HMM uses two-dimensional Discrete Cosine Transform (2DDCT) coefficients as the observation vectors opposite to previous HMM approaches which use pixel intensities to form the observation vectors. Our proposed system reduces the complexity of the training and recognition system. It offers a more flexible framework and can be used in real-time human-machine interactive applications. Experimental results demonstrate that the proposed approach is an effective method to recognize facial expression.