Human Mood Detection For Human Computer Interaction
This work addresses mood detection for HCI applications, but it is incremental as it builds on existing methods like SVM without introducing major innovations.
The paper tackled facial expression recognition for human-computer interaction by proposing an approach using skin filters, edge projection analysis, and SVM classification, achieving recognition of six basic expressions with an emphasis on fast execution.
In this paper we propose an easiest approach for facial expression recognition. Here we are using concept of SVM for Expression Classification. Main problem is sub divided in three main modules. First one is Face detection in which we are using skin filter and Face segmentation. We are given more stress on feature Extraction. This method is effective enough for application where fast execution is required. Second, Facial Feature Extraction which is essential part for expression recognition. In this module we used Edge Projection Analysis. Finally extracted features vector is passed towards SVM classifier for Expression Recognition. We are considering six basic Expressions (Anger, Fear, Disgust, Joy, Sadness, and Surprise)