Automatic Sign Detection with Application to an Assistive Robot

This paper explores automatic detection and classification of exit signs with the aim of enabling a service robot to assist the visually impaired with indoor navigation, inspired by a guide dog. The ultimate aim is to achieve autonomous indoor navigation using computer vision to identify navigational goals in an unfamiliar environment. In particular, we focus on the task of exiting a building by following exit signs that may include arrows that indicate where the next door or sign is located. The proposed method utilizes a deep learning framework, Faster R-CNN, to classify and localize exit signs in real time. The Faster R-CNN model achieved competitive results on more sizable dataset than existing approaches.