Emotional Recognition Through Facial Expression Using Support Vector Machine

The purpose of work is to recognize the emotions of people with speaking and hearing disabilities. These emotions shall be recognized from images of humans with such disabilities. Multiple features shall be used to recognize emotions. These features shall make use of color, edge and texture information. We are likely to use BSIF, HOG and color histograms in the proposed study. Due to the complexity, quality, and unpredictable nature of facial emotions, very precise facial expression recognition is still challenging. Many areas of emotion recognition remain unexplored, including the recognition of complex emotions made up of fundamental emotions and the understanding of emotions from facial expressions in people who have difficulty hearing and speaking. This study suggests a technique for reading the emotions of the deaf through their facial expressions. To achieve this, we suggest a cutting-edge architecture. Both films and photographs will be used to study the architecture. The suggested approach has a number of uses, including increasing the quality of life for those who have hearing and speech difficulties as well as rehabilitation for those with disabilities.