A fast visual map building method using video stream for visual-based indoor localization

Visual-based indoor localization have become a favored research area in recent years. It can be used inside a building where GPS signals are often not available. And due to its low deployment cost, visual-based indoor localization has been implemented in the complicated indoor environment. However, in order to increase the accuracy of indoor localization, the scale of image database should be as large as possible. The process of building a database that can be used for indoor localization is laborious. Thus, we propose a fast visual map building method for visual-based indoor localization, which takes fully use of convenience of video stream. Compared with existing image-based indoor localization system, the proposed system utilize video data is much more convenient. The experimental results show that the proposed method is applicable in the complicated indoor environment. The possibility of localization error less than 2 meters is nearly 70%. The error performance of the proposed method is slightly worse than the traditional method. Nevertheless, the proposed method can dramatically decrease the complexity of building a visual map.