A Distinct Approach for Human Face Emotion Detection Using PCA-BFO Method

Research on emotion has increased significantly over the past two decades with many fields contributing includingpsychology, neuroscience, endocrinology, medicine, hi story, sociology, and even computer science. The numerous theories that attempt to explain the origin, neurobiology, experience, and function of emotions have only fostered more intense research on this topic. Current areas of research in the concept of emotion include the development of materials that stimulate and elicit emotion. Recent discoveries suggest that emotions are intricately linked to other functions such as attention, perception, memory, decision making, and learning. In the field of Human Computer Interaction, audio and visual information are considered to be major indicators. In this paper, We explore a new method PCA-BFO for recognition of human emotional state from audiovisual features. Bacterial Foraging Optimization algorithm has been widely accepted as a global optimization algorithm of current interest for distributed optimization and control. In this paper this algorithm is combined with Principle Component Analysis. The audiovisual feature is used to classify the data into corresponding emotion using PCA-BFO method. Experimental results demonstrate the effectiveness of the proposed system and achieve the good overall recognition.