Paper Info
Title
Scene-based image retrieval by transitive matching
Abstract
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 cluster 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 distinctly (by up to 40%), particularly by the shortest path approach.
Year
DOI
Venue
2011
10.1145/1991996.1992043
ICMR
Keywords
Field
DocType
shortest path approach,retrieval score,target image,query image,scene-based image retrieval,shortest path,probabilistically motivated shortest path,transitive matching,targeted image collection,scene-based retrieval,image collection,image retrieval,similarity search
Computer vision,Automatic image annotation,Shortest path problem,Pattern recognition,Image texture,Computer science,Image retrieval,Artificial intelligence,Nearest neighbor search,Content-based image retrieval,Transitive relation,Visual Word
Conference
Citations 
PageRank 
References 
2
0.55
15
Authors
2
Name
Order
Citations
PageRank
Adrian Ulges132826.61
Christian Schulze215416.70