City-Scale Location Recognition

Grant Schindler, Matthew Brown, Richard Szeliski
2007 2007 IEEE Conference on Computer Vision and Pattern Recognition  
We look at the problem of location recognition in a large image dataset using a vocabulary tree. This entails finding the location of a query image in a large dataset containing 3 × 10 4 streetside images of a city. We investigate how the traditional invariant feature matching approach falls down as the size of the database grows. In particular we show that by carefully selecting the vocabulary using the most informative features, retrieval performance is significantly improved, allowing us to
more » ... ncrease the number of database images by a factor of 10. We also introduce a generalization of the traditional vocabulary tree search algorithm which improves performance by effectively increasing the branching factor of a fixed vocabulary tree.
doi:10.1109/cvpr.2007.383150 dblp:conf/cvpr/SchindlerBS07 fatcat:37vmsrh7vnbijkozey3wvms7zq