Emotion Detection for the Blind Using Deep Learning

Emotion detection for the blind using deep learning is a system designed to help visually impaired individuals recognize the facial expressions of people they are interacting with. The paper focuses on the development of a system that utilizes Local Binary Pattern (LBP) algorithm for face detection and transfer learning-aided MobileNetV2 model to classify emotions from facial expressions. Additionally, the system includes a hepatic and audio output feature that communicates the identified emotion to the visually impaired individual. The system is designed to work in real-time and is evaluated using a variety of performance metrics. This report provides a detailed analysis of the development and implementation of the system, as well as its performance and effectiveness in recognizing emotions accurately. The proposed system has the potential to improve the quality of life for visually impaired individuals by providing them with an additional means of communication and understanding emotional cues during social interactions.