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ICTIR
2009
Springer
15 years 7 months ago
A Four-Factor User Interaction Model for Content-Based Image Retrieval
In order to bridge the “Semantic gap”, a number of relevance feedback (RF) mechanisms have been applied to content-based image retrieval (CBIR). However current RF techniques i...
Haiming Liu 0002, Victoria S. Uren, Dawei Song, St...
CVPR
2006
IEEE
16 years 3 months ago
A Simple Bayesian Framework for Content-Based Image Retrieval
We present a Bayesian framework for content-based image retrieval which models the distribution of color and texture features within sets of related images. Given a userspecified ...
Katherine A. Heller, Zoubin Ghahramani
EDBT
2006
ACM
172views Database» more  EDBT 2006»
16 years 1 months ago
Fast Query Point Movement Techniques with Relevance Feedback for Content-Based Image Retrieval
Abstract. Target search in content-based image retrieval (CBIR) systems refers to finding a specific (target) image such as a particular registered logo or a specific historical ph...
Danzhou Liu, Kien A. Hua, Khanh Vu, Ning Yu
114
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VISUAL
2000
Springer
15 years 4 months ago
Shape Description for Content-Based Image Retrieval
Abstract. The present work is focused on a global image characterization based on a description of the 2D displacements of the different shapes present in the image, which can be e...
Edoardo Ardizzone, Antonio Chella, Roberto Pirrone
SSIAI
2000
IEEE
15 years 5 months ago
Lower-Level and Higher-Level Approaches to Content-Based Image Retrieval
This paper describes a content-based image retrieval system that employs both higher-level and lower-level vision methodologies separately and in conjunction for the retrieval of ...
Qasim Iqbal, Jake K. Aggarwal