EMOTION BASED RECOMMENDATION SYSTEM FOR VARIOUS APPLICATIONS

ECE

Most of the existing systems are highly complex in terms of time and storage for recognizing user behavior. This paper proposes an emotion based recommendation system for various applications that learns the emotions of the user from the camera. The human face acts as an important part in an individual’s body and helps in detection of one’s mood. The extracted input undergoes face detection, feature extraction, emotion recognition and application identification. The application includes playing music, videos, providing motivational quotes. This eliminates the time consuming and tedious task of manually segregating a playlist or searching for motivational quotes and videos. The experimental results are obtained by classifying the emotions using convolutional neural networks and support vector machine. The data are validated using testing and training method to obtain the exact emotion of the user. The applications are identified from the predicted emotions. By this way the emotions are analyzed and the required applications like playing music and motivational quotes are provided.

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