Performance Comparison of an Effectual Approach with K-Means Clustering Algorithm for the Recognition of Facial Expressions

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Provided by: International Journal of Computer Science and Mobile Computing (IJCSMC)
Topic: Data Management
Format: PDF
Automatic facial expressions recognition and classification has become active research field in image processing area over a last two decades. It has many applications like human computer interaction, face identification and videoconferencing. In this paper, two approaches are presented for the recognition of facial expressions from frontal facial expression images. The comparison of K-means clustering algorithm with proposed approach for facial expression recognition has done. This paper is to present a new approach that recognizes facial expressions automatically and also to show the effectual outcome of this approach over the existing K-means clustering approach.
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