Efficient Panorama Database Indexing for Indoor Localization
Jean-Baptiste Boin, Dmytro Bobkov, Eckehard G. Steinbach, Bernd Girod · 2019
We consider the task of indoor localization in large-scale environments using visual search on a database of geo-tagged panoramas. In this work we propose an efficient way to represent the database so as to maximize the search accuracy while minimizing the amount of computation required per query. The success of our method is due to a combination of (i) a hierarchical indexing method based on panorama image region information, and (ii) image descriptors aggregated from multiple views sampled finely over the panorama using generalized max pooling (GMP). Experiments on a large indoor dataset show that the complexity is reduced compared to common state-of-the-art retrieval methods such as FLANN (Fast Library for Approximate Nearest Neighbors): our scheme is more than twice as fast as an index based on FLANN while maintaining a similar retrieval performance.