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» Features for Image Retrieval: A Quantitative Comparison
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ICIP
1999
IEEE
14 years 9 months ago
In-Picture Search Algorithm for Content-Based Image Retrieval
Researchers are currently more interested in searching for fragments that are similar to a query, than a total data item that is similar to a query; the search interest is for &qu...
Punpiti Piamsa-nga, Nikitas A. Alexandridis, Sanan...
ICIP
2003
IEEE
14 years 9 months ago
Performance evaluation of Euclidean/correlation-based relevance feedback algorithms in content-based image retrieval systems
In this paper, we evaluate and investigate two main types of relevance feedback algorithms; the Euclidean and the correlation?based approaches. In the first case, we examine heuri...
Anastasios D. Doulamis, Nikolaos D. Doulamis
ICCV
2009
IEEE
15 years 14 days ago
Feature-Centric Efficient Subwindow Search
embedded in a sliding-window scheme. Such exhaustive search involves massive computation. Efficient Subwindow Search (ESS) [11] avoids this by means of branch and bound. However...
Alain Lehmann, Bastian Leibe, Luc van Gool
CIVR
2004
Springer
141views Image Analysis» more  CIVR 2004»
14 years 27 days ago
Natural Scene Retrieval Based on a Semantic Modeling Step
In this paper, we present an approach for the retrieval of natural scenes based on a semantic modeling step. Semantic modeling stands for the classification of local image regions...
Julia Vogel, Bernt Schiele
ICMCS
2008
IEEE
186views Multimedia» more  ICMCS 2008»
14 years 1 months ago
Dissimilarity measures for content-based image retrieval
Dissimilarity measurement plays a crucial role in contentbased image retrieval. In this paper, sixteen core dissimilarity measures are introduced and evaluated. We carry out a sys...
Rui Hu, Stefan M. Rüger, Dawei Song, Haiming ...