Scene-based Image Retrieval by Transitive Matching

Adrian Ulges, Christian Schulze
ACM International Conference on Multimedia Retrieval, Trento, Italy, o.A., 4/2011


We address scene-based image retrieval, the challenge of finding pictures taken at the same location as a given query image, whereas a key challenge lies in the fact that target images may show the same scene but different parts of it. To overcome this lack of direct correspondences with the query image, we study two strategies that exploit the structure of the targeted image collection: first, cluster matching, where pictures are grouped and retrieval is conducted on clus- ter level. Second, we propose a probabilistically motivated shortest path approach that determines retrieval scores based on the shortest path in a cost graph defined over the image collection. We evaluate both approaches on several datasets including indoor and outdoor locations, demonstrating that the accuracy of scene-based retrieval can be improved dis- tinctly (by up to 40%), particularly by the shortest path approach.




@inproceedings{ ULGE2011,
	Title = {Scene-based Image Retrieval by Transitive Matching},
	Author = {Adrian Ulges and Christian Schulze},
	BookTitle = {ACM International Conference on Multimedia Retrieval},
	Month = {4},
	Year = {2011},
	Publisher = {o.A.}

Last modified:: 30.08.2016