Image-Based Ego-Positioning

This thesis proposes an image-based ego-positioning framework to achieve sub-meter accuracy, with compact reference database compared to previous work, which can be used for the positioning of Internet connected devices. Consumer GPS devices nowadays obtain accuracy around several meters, which could be worse or even unable to work depending on the connection with GPS satellites. Current researches on image-based positioning utilize images and the reference database in different ways, however their accuracy, time consumption or database size have set limitations of their application. Experiments on different scenes in this work demonstrate that the method we proposed effectively reduce the size of reference database while main- taining a sub-meter accuracy for positioning. With evaluated performance, influencing factors are investigated, open problems are discussed for further improvements and applications.