A Context for Human Behavior Recognition Using Facial Expression

Human beings are born to show facial expressions, and this is the only behavior that identifies the specialty of a human being. This feature of humans makes him unique and expressive to handle different situations in real life. Even this feature of human beings makes him attractive and expressive. Doctors identify the psychiatric patient based on their facial expressions. The happiness, sadness, fear, anger are some major expressions given by human beings, when faces specific situations. This paper gives Facial Expression Recognition (FER) system which plays a pivotal role in enabling computers to understand human behavior through the analysis of facial expressions. In this research paper, a journey is to enhance FER systems are shown by leveraging advanced algorithms and methodologies. The purpose of this work is to enhance the accuracy and performance of FER models, thereby facilitating more empathetic and natural interactions between humans and machines. This work delves into the technical intricacies of FER, exploring innovative approaches such as convolutional neural networks and recurrent neural networks to decipher facial cues and recognize emotions more accurately. Additionally, challenges related to dataset diversity, real-world deployment, ethical considerations, and user experience, striving to create FER systems are identified that are not only technologically proficient but also respectful of individual privacy and cultural diversity. Through this research, the aim to pave the way for more empathetic and inclusive human-computer interactions, ultimately contributing to a future where technology enhances our understanding of emotions and strengthens human connections. It gives 79.2% better results than the previously proposed systems. This work could be effective in the field of medical, crime detection and other investigations systems too, this could be a drastic revolution to identify pain, happiness and other features using computers in the future.