Boost image clustering with user query log
Hao Cheng
Hua, K.A.
Ning Yu
Sch. of Electr. Eng. & Comput. Sci., Central Florida Univ., Orlando, FL;
This paper appears in: Multimedia and Expo, 2008 IEEE International Conference on
Publication Date: June 23 2008-April 26 2008
On page(s): 1241-1244
Location: Hannover,
ISBN: 978-1-4244-2570-9
INSPEC Accession Number: 10178944
Digital Object Identifier: 10.1109/ICME.2008.4607666
Current Version Published: 2008-08-26
Abstract
Image clustering is to derive a salient grouping of images such that similar ones are placed in the same cluster, which is useful in many applications. In this paper, we propose a constrained clustering algorithm, which leverages the collected user query log to guide the clustering process. Our method models a set of images as a graph and randomly contracts two vertices into a meta vertex iteratively with regarding to their similarity until the desired number of image groups has been reached. The experimental results demonstrate the superiority of our proposal.
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