Statistical modeling for image matching in large image databases
2011 (Engelska)Ingår i: 2011 International Conference on Internet of Things and 4th International Conference on Cyber, Physical and Social Computing, IEEE, 2011, s. 648-652Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]
Matching a query (reference) image to an image extracted from a database containing (possibly) transformed image copies is an important retrieval task. In this paper we present a general method based on matching densities of the corresponding image feature vectors by using the Bregman distances. We consider statistical estimators for some quEDratic entropy-type characteristics. In particular, the quEDratic Bregman distances can be evaluated in image matching problems whenever images are modeled by random feature vectors in large image databases. Moreover, this method can be used for average case analysis for optimization of joining large databases. © 2011 IEEE.
Ort, förlag, år, upplaga, sidor
IEEE, 2011. s. 648-652
Nyckelord [en]
Approximate matching, Asymptotic normality, Bregman distance, Database join, Image matching, Image retrieval
Nationell ämneskategori
Datorgrafik och datorseende
Identifikatorer
URN: urn:nbn:se:umu:diva-206417DOI: 10.1109/iThings/CPSCom.2011.117Scopus ID: 2-s2.0-84863239800ISBN: 9780769545806 (tryckt)OAI: oai:DiVA.org:umu-206417DiVA, id: diva2:1749159
Konferens
2011 IEEE International Conference on Internet of Things, iThings 2011 and 4th IEEE International Conference on Cyber, Physical and Social Computing, CPSCom 2011, Dalian, China, October 19-22, 2011
2023-04-052023-04-052025-02-07Bibliografiskt granskad