The proliferation of earth observation satellites, together with their continuously increasing performances, provides today a massive amount of geospatial data. Analysis and exploration of such data leads to various applications, from agricultural monitoring to crisis management and global security.
However, they also raise very challenging problems, e.g. dealing with extremely large and real time geospatial data, or user-friendly querying and retrieval satellite images or mosaics. The purpose of this special session is to address these challenges, and to allow researchers from multimedia retrieval and remote sensing to meet and share their experiences in order to build the remote sensing retrieval systems of tomorrow.
Topics of interest
- Content- and context-based indexing, search and retrieval of RS data
- Search and browsing on RS Web repositories to face the Peta/Zettabyte scale
- Advanced descriptors and similarity metrics dedicated to RS data
- Usage of knowledge and semantic information for retrieval in RS
- Maching learning for image retrieval in remote sensing
- Query models, paradigms, and languages dedicated to RS
- Multimodal / multi-obsevations (sensors, dates, resolutions) analysis of RS data
- HCI issues in RS retrieval and browsing
- Evaluation of RS retrieval systems
- High performance indexing algorithms for RS data
- Summarization and visualization of very large satellite image datasets
- Applications of image retrieval in remote sensing
Many public datasets are available to researchers and can be used to evaluate the contributions related to image retrieval in remote sensing. The UC Merced Land Use Dataset is of particular interest in this context, with 2100 RGB images, 21 classes (http://vision.ucmerced.edu/datasets/landuse.html).
Important dates
- Submission deadline: April, 7th
- Notification to authors: May, 12th
- Camera-ready deadline: May, 20th
Contact
For more information please contact the special session chairs Sébastien Lefèvre (sebastien.lefevre <at> irisa.fr) and Philippe-Henri Gosselin (gosselin <at> ensea.fr)