Geolocalization using mobile phone and street grid map in dynamic environment

We present a robust system for geolocalization in dynamic environments. Our application is a camera system designed to help the visually impaired navigate. It is also suitable for healthy eyesight users to find their way around unfamiliar areas. We combine visual odometry (VO) with the semantic information available in map to estimate the global coordinates of the walking users. In order to handle dynamic environments, our approach exploits the ground plane constraint in estimating the visual odometry. The motion estimation results are fed into a Monte Carlo Localization framework which localizes the user by matching the local motion trajectory with the shape of the street network found in the map. We validated our system with video sequences captured in different crowded urban environments. Experimental results show that our method not only corrects the cumulative drifting error but also manages to recover from serious visual odometry failure.