On-the-Fly Image Classification to Help Blind People
Dalal Aljasem, Michael Heeney, Armando Pesenti Gritti, Franco Raimondi · 2016
In this paper we present an affordable solution to help blind people navigate unknown environments. Our solution performs image classification on a Raspberry Pi and provides feedback to users by means of vibration motors to signal the presence of an obstacle in a given direction. The training phase is performed off-line, while the on-line phase can classify an image in 1.12 seconds on average. We provide an evaluation using several thousands images, showing that we can achieve a precision of 79% and a recall of 79%. All our code and the hardware design files are released open source.