An approach with CNN to unsafe manhole classification for visually impaired people

摘要

In this paper, manhole detection problem in pedestrian path from an image for visually impaired people or blind people is discussed. In many developing countries, it occurs many times in sidewalks that the manhole exists on the tactile paving surface and sometimes it is under construction or its cover keeps open. It means something unsafe for visually impaired or blind people or kids that they may fell in such manholes. So in this work, all manholes are divided into two types, which is respectively labeled as "normal" and "unsafe", and we propose a method for both detection and classification with convolutional neural network (CNN). Some experiments with actually existing manhole images in Mongolia showed that our method classifies two types of manhole effectively.