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ICTIR
2009
Springer
14 years 3 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
14 years 10 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»
14 years 8 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
VISUAL
2000
Springer
14 years 4 days 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
14 years 29 days 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