Performance Enhancement of Facial Expression Recognition using Appearance based features
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 6
Abstract
Ability of recognizing facial expression is important part of behavioural science, which helps to ease the communication. This ability can serve in many contexts. Hence, facial expression is an important research area over the last two decades. In this paper, describes the extraction of the minimum number of Gabor wavelet parameters for the recognition of facial expressions and work with facial components like eyes and mouth by using hierarchical approach. The objective of our research was to investigate the performance of a facial expression recognition system and less work with feature extraction to classify expression. This system recognizes basic seven expressions happy, sad, neutral, angry, surprise, fear and disgust. We present a hierarchy for facial region extraction from static image. For determination of face effective areas is used from bounding box. This method has high ability in intelligent selection of areas in facial expression recognition system. Using determination of effective areas classify expression directly. Remaining faces fed to Gabor filter and it further reduces by Principle Component Analysis (PCA) to classify expression using Euclidean distance. Results test on JAFFE database indicates that proposed system for facial expression recognition is good accuracy and generating superior results as compared to other approaches.
Authors and Affiliations
Jaimini Suthar, Mahesh Goyani
Keywords
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