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Terrain Object recognition and Context Fusion for Decision Support
Linköping University, Department of Computer and Information Science. Linköping University, The Institute of Technology.
2008 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

A laser radar can be used to generate 3D data about the terrain in a very high resolution. The development of new support technologies to analyze these data is critical to the effective and efficient use of these data in decision support systems, due to the large amounts of data that are generated. Adequate technology in this regard is currently not available and development of new methods and algorithms to this end are important goals of this work.

A semi-qualitative data structure for terrain surface modelling has been developed. A categorization and triangulation process has also been developed to substitute the high resolution 3D model for this data structure. The qualitative part of the structure can be used for detection and recognition of terrain features. The quantitative part of the structure is, together with the qualitative part, used for visualization of the terrain surface. Substituting the 3D model for the semi-qualitative structures means that a data reduction is performed.

A number of algorithms for detection and recognition of different terrain objects have been developed. The algorithms use the qualitative part of the previously developed semi-qualitative data structure as input. The taken approach is based on matching of symbols and syntactic pattern recognition. Results regarding the accuracy of the implemented algorithms for detection and recognition of terrain objects are visualized.

A further important goal has been to develop a methodology for determining driveability using 3D-data and other geographic data. These data must be fused with vehicle data to determine the properties of the terrain context of our operations with respect to driveability. This fusion process is therefore called context fusion. The recognized terrain objects are used together with map data in this method. The uncertainty associated with the imprecision of the data has been taken into account as well.

Place, publisher, year, edition, pages
Institutionen för datavetenskap , 2008. , 88 p.
Series
Linköping Studies in Science and Technology. Thesis, ISSN 0280-7971 ; 1371
Keyword [en]
nformation Fusion, Terrain Elevation Model, Driveability, Context Fusion, Terrain Object Recognition
National Category
Computer Science
Identifiers
URN: urn:nbn:se:liu:diva-11926ISBN: 978-91-7393-861-7 (print)OAI: oai:DiVA.org:liu-11926DiVA: diva2:18313
Presentation
2008-06-11, Alan Turing, Hus E, Campus Valla, Linköpings universitet, Linköping, 13:15 (English)
Opponent
Supervisors
Note
Report code: LiU-Tek-Lic-2008:29.Available from: 2008-05-27 Created: 2008-05-27 Last updated: 2009-05-05
List of papers
1. Dual Aspects of a Multi-Resolution Grid-Based Terrain Data Model with supplementary Irregular Data Points
Open this publication in new window or tab >>Dual Aspects of a Multi-Resolution Grid-Based Terrain Data Model with supplementary Irregular Data Points
2000 (English)In: Proceedings of the 3rd International Conference on Information Fusion, Paris, France, IEEE , 2000, Vol. 2, WED4/3-WED410 vol.2 p.Conference paper, Published paper (Refereed)
Abstract [en]

Digital terrain data models in high resolution are required in applications for visualization but also, e.g. for identification of various types of terrain features. These two aspects are in a way contradictory since the former application require a large number of data points to represent the high resolution, while the latter cannot deal with such a large number of data points without high demands for heavy computational powers. A solution to this problem is a structure that includes quantitative characteristics for visualization and a qualitative representation for feature analysis. A digital terrain data model characterized with these dual aspects has been designed and is presented in this work.

Place, publisher, year, edition, pages
IEEE, 2000
Keyword
data models, data visualisation, geographic information systems, spatial reasoning, terrain mapping, wavelet transforms
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13309 (URN)2-7257-0000-0 (ISBN)
Conference
Third International Conference on Information Fusion, 10-13 July 2000, Paris, France
Available from: 2008-05-27 Created: 2008-05-27 Last updated: 2015-01-13
2. Determination of Terrain Features in a Terrain Model from Laser Radar Data
Open this publication in new window or tab >>Determination of Terrain Features in a Terrain Model from Laser Radar Data
2003 (English)In: Proceedings of the ISPRS Working Group III/3 Workshop on 3D Reconstruction from Airborne Laser Scanner and InSAR Data, Dresden, Germany, 2003Conference paper, Published paper (Other academic)
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13310 (URN)
Available from: 2008-05-27 Created: 2008-05-27
3. Context Fusion for Driveability Analysis
Open this publication in new window or tab >>Context Fusion for Driveability Analysis
2005 (English)In: Proceedings of the 8th Int. Conf. on Information Fusion, Philadelphia Pennsylvania, USA, 2005, Vol. 2Conference paper, Published paper (Refereed)
Abstract [en]

Driveability analysis is a quite complex problem that for its solution depends on several factors. One of these factors concerns the type of vehicle for which a drive-way should be determined. Besides this, the terrain structure, the type of vegetation but also the ground type and its conditions play important roles. Driveability analysis will consequently include analysis of primarily geographical information and the outcome of this analysis can be used to support decision making in command and control systems. However, quite often the required geographical information is represented in a resolution that is either too low and/or is represented with a high degree of uncertainty that cannot be neglected. In this work, an approach to driveability analysis is presented in which geographical information is regarded as context information that eventually is fused to generate paths, that may be drivable for certain types of vehicles. This information is fused by means of a knowledge-based technique that determines the driveability from a set of qualitative driveability impact factors.

National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-13311 (URN)10.1109/ICIF.2005.1592002 (DOI)
Available from: 2008-05-27 Created: 2008-05-27

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Department of Computer and Information ScienceThe Institute of Technology
Computer Science

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