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» Features for Image Retrieval: A Quantitative Comparison
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ICIP
1999
IEEE
15 years 11 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
15 years 11 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
16 years 2 months 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
97
Voted
CIVR
2004
Springer
141views Image Analysis» more  CIVR 2004»
15 years 2 months 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»
15 years 4 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 ...