NDLI: Graph-Cut Transducers for Relevance Feedback in Content Based Image Retrieval

Content Provider	IEEE Xplore Digital Library
Author	Sahbi, H. Audibert, J.-Y. Keriven, R.
Copyright Year	2007
Description	Author affiliation: Ecole Nat. des Ponts et Chaussees, Paris (Sahbi, H.; Audibert, J.-Y.; Keriven, R.)
Abstract	Closing the semantic gap in content based image retrieval (CBIR) basically requires the knowledge of the user's intention which is usually translated into a sequence of questions and answers (Q&A). The user's feedback to these questions provides a CBIR system with a partial labeling of the data and makes it possible to iteratively refine a decision rule on the unlabeled data. Training of this decision rule is referred to as transductive learning. This work is an original approach to relevance feedback (RF) based on graph-cuts. Training consists in implicitly modeling the manifold enclosing both the labeled and unlabeled dataset and finding a partition of this manifold using a min-cut. The contribution of this work is two-fold (i) this is the first comprehensive study of relevance feedback using graph cuts and (ii) our RF model exploits the structure of the data manifold by considering also the structure of the unlabeled data. Experiments conducted on generic as well as specific databases show that our graph-cut based approach is very effective, outperforms other existing methods and makes it possible to converge to almost all the images of the user's "class of interest" with a very small labeling effort. A demo is available through our image retrieval tool kit (IRTK).
Starting Page	1
Ending Page	8
File Size	1028422
Page Count	8
File Format	PDF
ISBN	9781424416301
ISSN	15505499
DOI	10.1109/ICCV.2007.4408861
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-14
Publisher Place	Brazil
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Transducers Feedback Image retrieval Content based retrieval Radio frequency Displays Labeling Image databases Image converters Bayesian methods
Content Type	Text
Subject	Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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