AI Assistant for Visually Impaired

This paper presents an advanced assistive technol- ogy system aimed at improving accessibility and independence for visually impaired individuals. Utilizing artificial intelligence (AI) and computer vision techniques, the system provides real- time auditory feedback to users about their surroundings. The core components of the system include image captioning, face recognition, and depth estimation, all integrated to offer a comprehensive understanding of the environment. The system captures live video feed through a webcam, processes the images using pre-trained models like CLIPSeg for image segmentation and DPT for depth estimation, and generates textual descriptions of detected objects and their spatial distances. These descriptions are translated from English to Kannada using Google’s transla- tion services and converted into speech with the gTTS library, ensuring accessibility for Kannada-speaking users. Additionally, the system employs face recognition to identify known individuals in the vicinity, providing personalized auditory notifications. The combination of these technologies enables the system to offer context-aware assistance, helping visually impaired users to navigate and interact with their surroundings more effectively. Experimental results demonstrate the system’s capability to deliver accurate, real-time feedback, highlighting its potential to significantly enhance the quality of life for visually impaired individuals.