Image Descriptions for Visually Impaired Individuals to Locate Restroom Facilities - Cheng-Si He; Nan-Kai Lo; Yu-Huan Chien; Siao-Si Lin (Engineering Proceedings, 2025)
Since visually impaired individuals cannot observe their surroundings, they face challenges in accurately locating objects. Particularly in restrooms, where various facilities are spread across a limited space, the risk of tripping and being injured significantly increases. To prevent such accidents, individuals with visual impairments need help to navigate these facilities. Therefore, we designed a head-mounted device that utilized artificial intelligence (AI) to enhance its functionality. The ESP32-CAM was implemented to capture and transmit images to a computer. The images were then converted into a model-compatible format for the bootstrapping language-image pre-training (BLIP) model to process and generate English descriptions (i.e., written captions). Then, Google Text-to-Speech (gTTS) was employed to convert these descriptions into speech, which was delivered audibly through a speaker. The SacreBLEU and MOS scores indicated that the developed device produced relatively accurate, natural, and intelligible spoken directions. The device assists visually impaired individuals in navigating and locating the restroom facilities to a satisfactory level.