Human Feelings Identification using Facial Gesture

Abstract

This paper describes the approach for a real-time facial gesture is used for human feelings identification, human feelings Identification (HFI) is an essential research fields in computer visions and artificial intelligence systems. Human Face is an import part of the body; it is used for non-verbal communication. This paper proposes a practical working model of human feelings detection on a single as well as group feelings identification, and Group feeling identification is a challenging problem due to obscuration of the hidden body pose variation, occlusion, variable lighting condition, indoor-outdoor siting, image quality. The group feeling identification are used in crowd analytics’, social media, marking, social event detection, public safety, human computing interaction and many more area. The proposed method consists of two-stage of detection: Face detection and Feelings identification. A Haar cascade method is used for detection of the input images and videos; the web camera is used to capture the real-time images and videos. This research is beneficial in the different area of applications Medical, Army, Navy, Airport and multiplex for security and virtual learning environments. Deep learning algorithm along with machine learning convolution neural network provides state of the art solution to classification, classification- localization, object detection, instance segmentation and image captioning. The significate percentage of seven human feelings identification rate in the form of accuracy is improving in emotions identification as compared to the previous schemes.