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Ground Target Recognition using Rectangle Estimation
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.ORCID-id: 0000-0002-4434-8055
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
Linköpings universitet, Institutionen för systemteknik, Reglerteknik. Linköpings universitet, Tekniska högskolan.
2006 (engelsk)Inngår i: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 15, nr 11, s. 3400-3408Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We propose a ground target recognition method based on 3-D laser radar data. The method handles general 3-D scattered data. It is based on the fact that man-made objects of complex shape can be decomposed to a set of rectangles. The ground target recognition method consists of four steps; 3-D size and orientation estimation, target segmentation into parts of approximately rectangular shape, identification of segments that represent the target's functional/main parts, and target matching with CAD models. The core in this approach is rectangle estimation. The performance of the rectangle estimation method is evaluated statistically using Monte Carlo simulations. A case study on tank recognition is shown, where 3-D data from four fundamentally different types of laser radar systems are used. Although the approach is tested on rather few examples, we believe that the approach is promising.

sted, utgiver, år, opplag, sider
IEEE Signal Processing Society, 2006. Vol. 15, nr 11, s. 3400-3408
Emneord [en]
Automatic target recognition, Laser radar, Rectangle estimation
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-14120DOI: 10.1109/TIP.2006.881965OAI: oai:DiVA.org:liu-14120DiVA, id: diva2:22673
Tilgjengelig fra: 2006-11-06 Laget: 2006-11-06 Sist oppdatert: 2017-12-13
Inngår i avhandling
1. Ground Object Recognition using Laser Radar Data: Geometric Fitting, Performance Analysis, and Applications
Åpne denne publikasjonen i ny fane eller vindu >>Ground Object Recognition using Laser Radar Data: Geometric Fitting, Performance Analysis, and Applications
2006 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
Abstract [en]

This thesis concerns detection and recognition of ground object using data from laser radar systems. Typical ground objects are vehicles and land mines. For these objects, the orientation and articulation are unknown. The objects are placed in natural or urban areas where the background is unstructured and complex. The performance of laser radar systems is analyzed, to achieve models of the uncertainties in laser radar data.

A ground object recognition method is presented. It handles general, noisy 3D point cloud data. The approach is based on the fact that man-made objects on a large scale can be considered be of rectangular shape or can be decomposed to a set of rectangles. Several approaches to rectangle fitting are presented and evaluated in Monte Carlo simulations. There are error-in-variables present and thus, geometric fitting is used. The objects can have parts that are subject to articulation. A modular least squares method with outlier rejection, that can handle articulated objects, is proposed. This method falls within the iterative closest point framework. Recognition when several similar models are available is discussed.

The recognition method is applied in a query-based multi-sensor system. The system covers the process from sensor data to the user interface, i.e., from low level image processing to high level situation analysis.

In object detection and recognition based on laser radar data, the range value’s accuracy is important. A general direct-detection laser radar system applicable for hard-target measurements is modeled. Three time-of-flight estimation algorithms are analyzed; peak detection, constant fraction detection, and matched filter. The statistical distribution of uncertainties in time-of-flight range estimations is determined. The detection performance for various shape conditions and signal-tonoise ratios are analyzed. Those results are used to model the properties of the range estimation error. The detector’s performances are compared with the Cramér-Rao lower bound.

The performance of a tool for synthetic generation of scanning laser radar data is evaluated. In the measurement system model, it is possible to add several design parameters, which makes it possible to test an estimation scheme under different types of system design. A parametric method, based on measurement error regression, that estimates an object’s size and orientation is described. Validations of both the measurement system model and the measurement error model, with respect to the Cramér-Rao lower bound, are presented.

sted, utgiver, år, opplag, sider
Institutionen för systemteknik, 2006
Serie
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1055
Emneord
Laser radar, object detection, object recognition, performance, least squares, ICP, Cramér-Rao
HSV kategori
Identifikatorer
urn:nbn:se:liu:diva-7685 (URN)91-85643-53-X (ISBN)
Disputas
2006-11-17, BL32-Nobel, Campus Valla, Linköpings universitet, Linköping, 13:15 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2006-11-06 Laget: 2006-11-06 Sist oppdatert: 2016-08-31

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