Assistive Technology for Visually Impaired using Tensor Flow Object Detection in Raspberry Pi and Coral USB Accelerator
Amit Ghosh, Shamsul Arefeen Al Mahmud, Thajid Ibna Rouf Uday, Dewan Md. Farid
Abstract
Assistive Technology (AT) becomes an interesting field of research in this present era. According to the World Health Organisation (WHO - https://www.who.int), there are approximately 285 million visually impaired people around the world. To address this issue, many researchers are employing new technologies, e.g. Machine Learning (ML), Computer Vision (CV), Image Processing, etc. This paper aims to develop an assistive technology based on Computer Vision, Machine Learning and Tensor Flow to support visually impaired people. The proposed system will allow the users to navigate independently using real-time object detection and identification. Hardware implementation is done to test the performance of the system, and the performance is tracked using a monitoring server. The system is developed on Raspberry pi 4 and a dedicated server with NVIDIA Titan X graphics where Google coral USB accelerator is used to boost processing power.