Posture estimation for the visually impaired people using human skeleton with a white cane

Abstract

Visually impaired people avoid dangers by using a white cane. Because they use it as an extension of their arm, we consider it a part of their body. Our goal is to recognize visually impaired people using a white cane in images and how they use it. We propose a method to estimate the posture of a person with a white cane by extending an existing posture estimation model: OpenPose. In our method, we incorporate a white cane as a part of the human skeleton model. We constructed a database of images of visually impaired people with a white cane to train the network for the extended human skeleton model. We develop a method to determine the left or right hand that holds the white cane in the training images because it is necessary to train right-handed and left-handed users separately. We can analyze the motion of the white cane by the result of posture estimation. We focus on the angle of the white cane and analyze its swing frequency. Throughout our experiments, we confirmed that our preliminary system successfully estimated the human posture with the white cane and the swing frequency of the white cane.