Spatial Representation to Support Visual Impaired People

The rapid development of Information and Communication Technology (ICT) enhances the government services to its citizen. As a consequence affects the exchange of information between citizen and government. However, some groups can experience some difficulties accessing the government services due to disabilities, such as blind people as well as material and geographical constraints. This paper aims to introduce a novel approach for place recognition to help the blind people to navigate inside a government building based on the correlation degree for the covariance feature vectors. However, this approach faces several challenges. One of the fundamental challenges inaccurate indoor place recognition for the visual impaired people is the presence of similar scene images in different places in the environmental space of the mobile robot system, such as a computer or office table in many rooms. This problem causes bewilderment and confusion among different places. To overcome this, the local features of these image scenes should be represented in more discriminatory and robustly way. However, to perform this, the spatial relation of the local features should be considered. The findings revealed that this approach has a stable manner due to its reliability in the place recognition for the robot localization. Finally, the proposed Covariance approach gives an intelligent way for visual place people localization through the correlation of Covariance feature vectors for the scene images.