Recognizing Elevator Buttons and Labels for Blind Navigation

Abstract

In this paper, we propose a method to detect elevator buttons and recognize their labels from images for blind navigation. First, a pixel-level mask of elevator buttons is segmented based on fully convolutional networks. Then a fast scene text detector is applied to recognize the text labels in the image as well as to extract their spatial vectors. Finally, all the detected buttons and their associated labels are paired by combining the button mask and spatial vectors of labels based on their location distribution. To evaluate the proposed method, we collect an elevator button dataset that contains 1,000 images with buttons captured from both inside and outside of elevators and annotate the locations and labels of all buttons. Preliminary results demonstrate the robustness and effectiveness of the proposed method for elevator button detection and associated label recognition.