|Title||Towards accurate camera geopositioning by image matching|
|Publication Type||Conference Paper|
|Authors||Imbriaco, R, Sebastian, C, Bondarev, E, de With, PHN|
|Conference Name||International Conference of Machine Vision|
|Conference Location||Munich, Germany|
|Keywords||Convolutional Neural Networks, Geopositioning, Image Matching, Panoramic Images, Visual Place Recognition|
In this work, we present a camera geopositioning system based on matching a query image against a database with panoramic images. For matching, our system uses memory vectors aggregated from global image descriptors based on convolutional features to facilitate fast searching in the database. To speed up searching, a clustering algorithm is used to balance geographical positioning and computation time. We refine the obtained position from the query image using a new outlier removal algorithm. The matching of the query image is obtained with a recall@5 larger than 90% for panorama-to-panorama matching. We cluster available panoramas from geographically adjacent locations into a single compact representation and observe computational gains of approximately 50% at the cost of only a small (approximately 3%) recall loss. Finally, we present a coordinate estimation algorithm that reduces the median geopositioning error by up to 20%.
Towards accurate camera geopositioning by image matching