Discovering favorite views of popular places with iconoid shift

Tobias Weyand, Bastian Leibe
2011 2011 International Conference on Computer Vision  
In this paper, we propose a novel algorithm for automatic landmark building discovery in large, unstructured image collections. In contrast to other approaches which aim at a hard clustering, we regard the task as a mode estimation problem. Our algorithm searches for local attractors in the image distribution that have a maximal mutual homography overlap with the images in their neighborhood. Those attractors correspond to central, iconic views of single objects or buildings, which we
more » ... y extract using a medoid shift search with a novel distance measure. We propose efficient algorithms for performing this search. Most importantly, our approach performs only an efficient local exploration of the matching graph that makes it applicable for large-scale analysis of photo collections. We show experimental results validating our approach on a dataset of 500k images of the inner city of Paris.
doi:10.1109/iccv.2011.6126361 dblp:conf/iccv/WeyandL11 fatcat:7ctkb7tkpnc7hk2egh4nhcqpzu