Rajesh A. Patil

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This paper introduces a method for automatic facial expression recognition in image sequences, which make use of Candide wire frame model and active appearance algorithm for tracking, and support vector machine for classification. Candide wire frame model is adapted properly on the first frame of face image sequence. Facial features in subsequent frames of(More)
Detection and location of the face as well as extraction of facial features from images is an important stage for numerous facial image interpretation tasks. Detection of facial feature points, such as corners of eyes, lip corners, nostrils from the images are crucial. In this paper a method for autormatic facial feature point detection in image sequences,(More)
This paper proposes a method for facial expression recognition in image sequences. Face is detected from the scene and then facial features are detected using image normalization, and thresholding techniques. Using an optimization algorithm the Candide wire frame model is adapted properly on the first frame of face image sequence. In the subsequent frames(More)
A method for automatic facial expression recognition in image sequences, is introduced which make use of Candide wire frame model and active appearance algorithm for tracking, and Bayesian classifier for classification. On the first frame of face image sequence, Candide wire frame model is adapted properly. In subsequent frames of image sequence, facial(More)
For human beings, facial expression is one of the most powerful and natural way to communicate their emotions and intensions. A human being can detect facial expressions without effort, but for a machine it is very difficult. Automatic facial expression recognition is an interesting and challenging problem. Automatic facial expression recognition systems(More)
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