Recognition of Human Facial Expression using Machine Learning Algorithm

In the vision of the computer, Human Action Recognition (HAR) plays a huge role in the research area. The human facial expressions convey a lot of information visually rather than articulately. Hence, to identify these facial expression by computer with high recognition rate was a challenging task. To overcome these problem, this paper presents a new technique for human face recognition using the real time videos. The aim of this paper is to recognize the Human Facial Expression like joy, sadness, surprise, fear, anger and disgust from the input video having homogeneous background. The extracted features are given to the pre-processing stage to remove noise and the required features are obtained from the Pre-loaded video sequence. For this gage of work we are using Viola-Jones Algorithm to recognize face, matching algorithms is used for training data, Extreme Sparse Learning and Kernel Extreme Sparse Learning algorithm to recognize the expression of human face. The main application of this works are information security, authentication, biometric identification, video surveillance, data privacy, Human Action Recognition (HAR), Human Computer Interface (HCI), Health Care etc. It also presents the application of the machine learning algorithm to recognize and classification of facial expressions in real time video. Here the pre-loaded video sequence of the human facial expression is given as the input to the MATLAB software to obtain the ideal output. This paper can be implemented using the High Configuration MATLAB simulation software.