Facial Expression Recognition

Computer Engineering

Facial Expressions are considered as one of the channels that convey human emotions. The task of emotion recognition often involves the analysis of human expressions in multi-modal forms such as images, text, audio or video. Different emotion types are identified through the integration of features from facial expressions. This information contains particular feature points that are used to analyse expressions or emotions of the person. These feature points are extracted using image processing techniques. The proposed system focuses on categorizing the set of 68 feature points into one of the six universal emotions i.e. Happy, Sad, Anger, Disgust, Surprise and Fear. For collecting these points, a series of images is given as input to the system. Feature points are extracted and corresponding co-ordinates of the points are obtained. Based on the distances co-ordinates from centroid, images are classified into one of the universal emotions. Existing system show recognition accuracy more than 90% when SVM (Support Vector Machine) classifier is used. In proposed system, SVM classifier is used for building the classification model using extracted 68 feature points from 7 Region of Interests (ROI). Proposed system recognizes emotions of the person with high precision.

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