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» An active feedback framework for image retrieval
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PRIS
2001
14 years 10 months ago
Relevance Feedback in Content-based Image Search
: Content-based image retrieval (CBIR) is a research area dedicated to address the retrieve and search multimedia documents for digital libraries. Relevance feedback is a powerful ...
HongJiang Zhang
MIR
2006
ACM
223views Multimedia» more  MIR 2006»
15 years 3 months ago
Adaptive image retrieval using a Graph model for semantic feature integration
The variety of features available to represent multimedia data constitutes a rich pool of information. However, the plethora of data poses a challenge in terms of feature selectio...
Jana Urban, Joemon M. Jose
160
Voted
BDA
2007
14 years 11 months ago
Hyperplane Queries in a Feature-Space M-tree for Speeding up Active Learning
In content-based retrieval, relevance feedback (RF) is a noticeable method for reducing the “semantic gap” between the low-level features describing the content and the usually...
Michel Crucianu, Daniel Estevez, Vincent Oria, Jea...
CVPR
2006
IEEE
15 years 11 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
CIVR
2008
Springer
173views Image Analysis» more  CIVR 2008»
14 years 11 months ago
Adaptive multiple feedback strategies for interactive video search
In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relev...
Huan-Bo Luan, Yantao Zheng, Shi-Yong Neo, Yongdong...