Efficient structure from motion with weak position and orientation priors

In this paper we present an approach that leverages prior information from global positioning systems and inertial measurement units to speedup structure from motion computation. We propose a view selection strategy that advances vocabulary tree based coarse matching by also considering the geometric configuration between weakly oriented images. Furthermore, we introduce a fast and scalable reconstruction approach that relies on global rotation registration and robust bundle adjustment. Real world experiments are performed using data acquired by a micro aerial vehicle attached with GPS/INS sensors. Our proposed algorithm achieves orientation results that are sub-pixel accurate and the precision is on a par with results from incremental structure from motion approaches. Moreover, the method is scalable and computationally more efficient than previous approaches.