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HEAT Image Retrieval System

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HEAT is an image retrieval web-application that is intended for large unstructured collections of images without semantic annotations. The system implements a novel searching paradigm that does not require any explicit query. At each iteration, the system displays a small set of images and the user chooses the image that best matches what she is looking for. After a few iterations, the sets of displayed images are gradually concentrated on images that satisfy the user.

This page contains the source code of the HEAT image retrieval web-application. The code can be used to reproduce the experimental results presented in the papers mentioned below. If you use this source, please cite one of those papers.

Related publications:

1. Iterative Relevance Feedback with Adaptive Exploration/Exploitation Trade-off , Nicolae Suditu and François Fleuret (Bibtex).

2. HEAT: Iterative Relevance Feedback with One Million Images, Nicolae Suditu and François Fleuret (BibTeX).


A demo web-server is available on-line at

screen shot demo imr

You can download the archive here: heat-2.0.tar.gz (6.68MB).

To run the application: extract the archive and follow the instructions in the README file.

The source code is copyright Idiap Research Institute and provided under the GNU Affero General Public License version 3 (AGPLv3).

Please contact Nicolae Suditu for comments and bug reports.

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Resource Information
Resource type: software
Date: Nov 29, 2011
Size: 6.7Mo
Access: Web
Ownership: Idiap Research Institute
Distribution: Web
Contact: François FLEURET
+41 277 217 739