DocumentCode :
1282907
Title :
Boosting Object Retrieval With Group Queries
Author :
Chen, Yanzhi ; Li, Xi ; Dick, Anthony ; Van den Hengel, Anton
Author_Institution :
Sch. of Comput. Sci., Univ. of Adelaide, Adelaide, SA, Australia
Volume :
19
Issue :
11
fYear :
2012
Firstpage :
765
Lastpage :
768
Abstract :
Given a query image of an object, object retrieval aims to return all images from a corpus that depict the same object. Inevitably, the accuracy of the result depends strongly on the quality of the query image. Several measures have been taken to improve retrieval result quality, including the addition of a bounding box to the query, the mining of highly ranked results for more views of the object, and spatial consistency re-ranking. In this letter, we propose a discriminative criterion for improving result quality. This criterion lends itself to the addition of extra query data, and we show that multiple query images can be combined to produce enhanced results. Experiments compare the performance of the method to state-of-the-art in object retrieval, and show how performance is lifted by the inclusion of further query images.
Keywords :
image representation; image retrieval; discriminative criterion; group query data; image enhancement; image quality; image retrieval; object query image; object retrieval; spatial consistency reranking; Accuracy; Adaptation models; Boosting; Support vector machines; Training; Vectors; Visualization; Discriminative ranking function; group query; object retrieval;
fLanguage :
English
Journal_Title :
Signal Processing Letters, IEEE
Publisher :
ieee
ISSN :
1070-9908
Type :
jour
DOI :
10.1109/LSP.2012.2216875
Filename :
6297999
Link To Document :
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