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Klasén, Lena
Publications (3 of 3) Show all publications
Ahlberg, J., Folkesson, M., Grönwall, C., Horney, T., Jungert, E., Klasén, L. & Ulvklo, M. (2006). Ground Target Recognition in a Query-Based Multi-Sensor Information System. Linköping, Sweden: Department of Electrical Engineering
Open this publication in new window or tab >>Ground Target Recognition in a Query-Based Multi-Sensor Information System
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2006 (English)Report (Other academic)
Abstract [en]

We present a system covering the complete process for automatic ground target recognition, from sensor data to the user interface, i.e., from low level image processing to high level situation analysis. The system is based on a query language and a query processor, and includes target detection, target recognition, data fusion, presentation and situation analysis. This paper focuses on target recognition and its interaction with the query processor. The target recognitionis executed in sensor nodes, each containing a sensor and the corresponding signal/image processing algorithms. New sensors and algorithms are easily added to the system. The processing of sensor data is performed in two steps; attribute estimation and matching. First, several attributes, like orientation and dimensions, are estimated from the (unknown but detected) targets. These estimates are used to select the models of interest in a matching step, where the targetis matched with a number of target models. Several methods and sensor data types are used in both steps, and data is fused after each step. Experiments have been performed using sensor data from laser radar, thermal and visual cameras. Promising results are reported, demonstrating the capabilities of the target recognition algorithms, the advantages of the two-level data fusion and the query-based system.

Place, publisher, year, edition, pages
Linköping, Sweden: Department of Electrical Engineering, 2006. p. 29
Series
LiTH-ISY-R, ISSN 1400-3902 ; 2748
Keywords
Multi-sensor fusion, Query languages, Infrared sensors, Laser radar, Range data, Target recognition, Target detection
National Category
Control Engineering
Identifiers
urn:nbn:se:liu:diva-14124 (URN)LiTH-ISY-R-2748 (ISRN)
Available from: 2006-11-06 Created: 2006-11-06 Last updated: 2016-08-31Bibliographically approved
Ahlberg, J. & Klasén, L. (2005). Surveillance Systems for Urban Crisis Management. In: : . Paper presented at Swedish Symposium on Image Analysis (SSBA), Malmö, Sweden, 10-11 mars 2005 (pp. 41-44). Swedish Society for automated image analysis
Open this publication in new window or tab >>Surveillance Systems for Urban Crisis Management
2005 (English)Conference paper, Published paper (Other academic)
Abstract [en]

We present a concept for combing 3D models and multiple heterogeneous sensors into a surveillance system enabling superior situation awareness. The concept has many military as well as civilian applications. A key issue is the use of a 3D environment model of the area to be surveyed, typically an urban area. In addition to the 3D model, the area of interest is monitored over time using multiple heterogeneous sensors, such as optical, acoustic, and/or seismic sensors. Data and analysis results from the sensors are visualized in the 3D model, thus putting them in a common reference frame and making their spatial and temporal relations obvious. The result is highlighted by an example where data from different sensor systems is integrated in a 3D model of a Swedish urban area.

Place, publisher, year, edition, pages
Swedish Society for automated image analysis, 2005
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-120561 (URN)
Conference
Swedish Symposium on Image Analysis (SSBA), Malmö, Sweden, 10-11 mars 2005
Available from: 2015-08-14 Created: 2015-08-14 Last updated: 2018-01-11Bibliographically approved
Horney, T., Ahlberg, J., Grönwall, C., Folkesson, M., Silvervarg, K., Fransson, J., . . . Ulvklo, M. (2004). An information system for target recognition. In: Belur V. Dasarathy (Ed.), Volume 5434 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications: . Paper presented at Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications, Orlando, FL, USA, April 12, 2004 (pp. 163-175). SPIE - International Society for Optical Engineering
Open this publication in new window or tab >>An information system for target recognition
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2004 (English)In: Volume 5434 Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications / [ed] Belur V. Dasarathy, SPIE - International Society for Optical Engineering, 2004, p. 163-175Conference paper, Published paper (Refereed)
Abstract [en]

We present an approach to a general decision support system. The aim is to cover the complete process for automatic target recognition, from sensor data to the user interface. The approach is based on a query-based information system, and include tasks like feature extraction from sensor data, data association, data fusion and situation analysis. Currently, we are working with data from laser radar, infrared cameras, and visual cameras, studying target recognition from cooperating sensors on one or several platforms. The sensors are typically airborne and at low altitude. The processing of sensor data is performed in two steps. First, several attributes are estimated from the (unknown but detected) target. The attributes include orientation, size, speed, temperature etc. These estimates are used to select the models of interest in the matching step, where the target is matched with a number of target models, returning a likelihood value for each model. Several methods and sensor data types are used in both steps. The user communicates with the system via a visual user interface, where, for instance, the user can mark an area on a map and ask for hostile vehicles in the chosen area. The user input is converted to a query in ΣQL, a query language developed for this type of applications, and an ontological system decides which algorithms should be invoked and which sensor data should be used. The output from the sensors is fused by a fusion module and answers are given back to the user. The user does not need to have any detailed technical knowledge about the sensors (or which sensors that are available), and new sensors and algorithms can easily be plugged into the system.

Place, publisher, year, edition, pages
SPIE - International Society for Optical Engineering, 2004
Series
Proceedings of SPIE, ISSN 0277-786X ; 5434
Keywords
Target recognition ; Sensors ; Interfaces ; Algorithms ; Automatic target recognition ; Cameras ; Data fusion ; Decision support systems ; Feature extraction ; Infrared cameras
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:liu:diva-120917 (URN)10.1117/12.540968 (DOI)
Conference
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications, Orlando, FL, USA, April 12, 2004
Available from: 2015-08-31 Created: 2015-08-31 Last updated: 2018-01-11Bibliographically approved
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