Human behavioural identification in different aspects using neural network

Examining a person’s facial expressions is a common technique for understanding their emotions, but training a computer to perform the same task is a difficult challenge. Numerous algorithms and methods are available to analyze human emotions conveyed through facial expressions. This study compares various approaches to recognizing emotions on human faces, incorporating multiple perspectives on emotion detection and utilizing the "Viola-Jones Face Detection" method to identify faces. Emotion classification can be accomplished using different classifiers, with features extracted through methods such as "Zernike moments," "DCT transform," or "LBP." Another method for identifying facial emotions is through Convolutional Neural Networks (CNN), which involves two stages. The first stage isolates the facial component vector, while the second stage removes the image’s background. With computer vision technology, it is now feasible to detect emotions by examining human faces using various algorithms and methods.