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Immersive Visualization of Visual Data Using Nonnegative Matrix Factorization

Babaee, Mohammadreza and Tsoukalas, Stefanos and Rigoll, Gerhard and Datcu, Mihai (2015) Immersive Visualization of Visual Data Using Nonnegative Matrix Factorization. Neurocomputing, 173 (2), pp. 245-255. Elsevier. ISSN 0925-2312

Full text not available from this repository.

Official URL: http://www.sciencedirect.com/science/article/pii/S0925231215012606

Abstract

Over the last two decades, dimension reduction for visualization has gained a high amount of attention in visual data mining where the data is represented by high-dimensional features. Basically, this approach leads to an unbalanced and occluded distribution of visual data in display space, giving rise to difficulties in browsing the data. In this paper we propose an approach for the visualization of image collections in such a way as (1) images are not occluded by each other, and the provided space is used as much as possible; (2) the similar images are positioned close together; (3) an overview of data is feasible. To fulfill these requirements, we propose to use regularized Nonnegative Matrix Factorization (NMF) controlled by parameters to reduce the dimensionality of data. Experiments performed on optical and radar images confirm the flexibility of proposed method in visualizing large-scale visual data. Finally, an immersive 3D virtual environment is suggested, to visualize the images, to allow the user to navigate and explore the data.

Item URL in elib:https://elib.dlr.de/100125/
Document Type:Article
Title:Immersive Visualization of Visual Data Using Nonnegative Matrix Factorization
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Babaee, MohammadrezaTechnical University Munich, GermanyUNSPECIFIED
Tsoukalas, StefanosTechnical University Munich, GermanyUNSPECIFIED
Rigoll, GerhardTechnical University Munich, GermanyUNSPECIFIED
Datcu, MihaiDLRUNSPECIFIED
Date:2015
Journal or Publication Title:Neurocomputing
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:173
Page Range:pp. 245-255
Editors:
EditorsEmail
Heskes, Tomt.heskes@science.ru.nl
Publisher:Elsevier
ISSN:0925-2312
Status:Published
Keywords:Data Visualization, Nonnegative Matrix Factorization
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben hochauflösende Fernerkundungsverfahren
Location: Oberpfaffenhofen
Institutes and Institutions:Remote Sensing Technology Institute > Photogrammetry and Image Analysis
Deposited By: Schwarz, Gottfried
Deposited On:30 Nov 2015 10:38
Last Modified:06 Sep 2019 15:18

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