%0 Conference Proceedings
%T Immersive Interactive Information Mining with Application to Earth Observation Data Retrieval
%+ Institute for Human Machine Communication [München]
%+ Munich Aerospace [Taufkirchen]
%A Babaee, Mohammadreza
%A Rigoll, Gerhard
%A Datcu, Mihai
%Z Part 1: Cross-Domain Conference and Workshop on Multidisciplinary Research and Practice for Information Systems (CD-ARES 2013)
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 1st Cross-Domain Conference and Workshop on Availability, Reliability, and Security in Information Systems (CD-ARES)
%C Regensburg, Germany
%Y Alfredo Cuzzocrea
%Y Christian Kittl
%Y Dimitris E. Simos
%Y Edgar Weippl
%Y Lida Xu
%I Springer
%3 Availability, Reliability, and Security in Information Systems and HCI
%V LNCS-8127
%P 376-386
%8 2013-09-02
%D 2013
%K Immersive visualization
%K Information mining
%K Dimension reduction
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X The exponentially increasing amount of Earth Observation (EO) data requires novel approaches for data mining and exploration. Visual analytic systems have made valuable contribution in understanding the structure of data by providing humans with visual perception of data. However, these systems have limitations in dealing with large-scale high-dimensional data. For instance, the limitation in dimension of the display screen prevents visualizing high-dimensional data points. In this paper, we propose a virtual reality based visual analytic system, so called Immersive Information Mining, to enable knowledge discovery from the EO archive. In this system, Dimension Reduction (DR) techniques are applied to high-dimensional data to map into a lower-dimensional space to be visualized in an immersive 3D virtual environment. In such a system, users are able to navigate within the data volume to get visual perception. Moreover, they can manipulate the data and provide feedback for other processing steps to improve the performance of data mining system.
%G English
%2 https://inria.hal.science/hal-01506787/document
%2 https://inria.hal.science/hal-01506787/file/978-3-642-40511-2_27_Chapter.pdf
%L hal-01506787
%U https://inria.hal.science/hal-01506787
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-TC9
%~ IFIP-TC8
%~ IFIP-CD-ARES
%~ IFIP-WG8-4
%~ IFIP-WG8-9
%~ IFIP-LNCS-8127