Face Recognition Using Raspberry PI for Mentally Retarded Person

Abstract

The face recognition system described in this paper focuses on addressing the needs of individuals with intellectual disabilities. Intellectual disabilities often affect an individual's cognitive and adaptive functioning, making it challenging for them to perform everyday tasks independently. This system utilizes the capabilities of Raspberry Pi , a low cost single-board computer, to create an accessible and user-friendly solution for face recognition. The main objective of this system is to assist mentally challenged individuals in recognizing and identifying familiar faces. By utilizing face recognition technology, the system aims to enhance their independence, social interactions, and overall quality of life. The Raspberry Pi platform provides a flexible and affordable hardware foundation for implementing this system. The system leverages a pre-trained deep learning model for face recognition, such as OpenCV or dlib, to perform face detection and identification tasks. The model is trained on a dataset containing facial images of familiar individuals to ensure accurate recognition. Raspberry Pi's computational capabilities enable real-time processing of the captured video feed, facilitating prompt recognition and response.