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International Symposium on Photoelectronic Detection and Imaging 2009: Laser Sensing and Imaging

作者： Armbruster, Walter FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

ISBN: (纸本)9780819476630

Practically no applications exist for which automatic processing of 2D intensity imagery can equal human visual perception. This is not the case for range imagery. The paper gives examples of 3D laser radar applications, for which automatic data processing can exceed human visual cognition capabilities and describes basic processing techniques for attaining these results. The examples are drawn from the fields of helicopter obstacle avoidance, object detection in surveillance applications, object recognition at high range, multi-object-tracking, and object re-identification in range image sequences. Processing times and recognition performances are summarized. The techniques used exploit the bijective continuity of the imaging process as well as its independence of object reflectivity, emissivity and illumination. This allows precise formulations of the probability distributions involved in figure-ground segmentation, feature-based object classification and model based object recognition. The probabilistic approach guarantees optimal solutions for single images and enables Bayesian learning in range image sequences. Finally, due to recent results in 3D-surface completion, no prior model libraries are required for recognizing and re-identifying objects of quite general object categories, opening the way to unsupervised learning and fully autonomous cognitive systems. © 2009 SPIE.

关键词： Object recognition

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Validation of the thermal code of RadTherm-IR, IR-workbench and F-TOM

Validation of the thermal code of RadTherm-IR, IR-workbench ...

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Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XX

作者： Schwenger, Frédéric Grossmann, Peter Malaplate, Alain Research Institute for Optronics and Pattern Recognition FGAN-FOM Gutleuthausstr. 1 76275 Ettlingen Germany

ISBN: (纸本)9780819475664

System assessment by image simulation requires synthetic scenarios that can be viewed by the device to be simulated. In addition to physical modeling of the camera, a reliable modeling of scene elements is necessary. Software products for modeling of target data in the IR should be capable of (i) predicting surface temperatures of scene elements over a long period of time and (ii) computing sensor views of the scenario. For such applications, FGAN-FOM acquired the software products RadTherm-IR (ThermoAnalytics Inc., Calumet, USA) and IR-Workbench (OKTAL-SE, Toulouse, France). Inspection of the accuracy of simulation results by validation is necessary before using these products for applications. In the first step of validation, the performance of both "thermal solvers" was determined through comparison of the computed diurnal surface temperatures of a simple object with the corresponding values from measurements. CUBI is a rather simple geometric object with well known material parameters which makes it suitable for testing and validating object models in IR. It was used in this study as a test body. Comparison of calculated and measured surface temperature values will be presented, together with the results from the FGAN-FOM thermal object code F-TOM. In the second validation step, radiances of the simulated sensor views computed by RadTherm-IR and IR-Workbench will be compared with radiances retrieved from the recorded sensor images taken by the sensor that was simulated. Strengths and weaknesses of the models RadTherm-IR, IR-Workbench and F-TOM will be discussed. ©2009 SPIE.

关键词： Surface temperature

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Protection of optical systems against laser radiation

Protection of optical systems against laser radiation

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Electro-Optical and Infrared Systems: Technology and Applications VI

作者： Ritt, G. Dengler, S. Eberle, B. FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

ISBN: (纸本)9780819477873

Both the increasing use of laser devices on the battlefield and the misuse of laser devices in civil environments (e.g. dazzling of pilots during approach) necessitate laser protection devices. Conventional laser protection filters based on absorption or interference effects only work in narrow wavelength bands and are usually not neutral in colour. Thus, they are not appropriate for such scenarios. Optical power limiting devices based on nonlinear optical effects (nonlinear absorption, nonlinear refraction, induced scattering) were proposed to offer broadband laser protection without disturbing the visual colour impression. Usually, optical nonlinear materials are examined in laboratory setups which are different from realistic optical systems. We report on the integration of nonlinear laser protection devices into different optical systems to prove the performance of limiting for commonly used optical systems. © 2009 SPIE.

关键词： Laser safety

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Model-based object recognition in range imagery

Model-based object recognition in range imagery

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Electro-Optical and Infrared Systems: Technology and Applications VI

作者： Armbruster, Walter FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

ISBN: (纸本)9780819477873

The paper formulates the mathematical foundations of object discrimination and object re-identification in range image sequences using Bayesian decision theory. Object discrimination determines the unique model corresponding to each scene object, while object re-identification finds the unique object in the scene corresponding to a given model. In the first case object identities are independent;in the second case at most one object exists having a given identity. Efficient analytical and numerical techniques for updating and maximizing the posterior distributions are introduced. Experimental results indicate to what extent a single range image of an object can be used for re-identifying this object in arbitrary scenes. Applications including the protection of commercial vessels against piracy are discussed. © 2009 SPIE.

关键词： Object recognition

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Improved target detection by IR dual-band image fusion

Improved target detection by IR dual-band image fusion

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Electro-Optical and Infrared Systems: Technology and Applications VI

作者： Adomeit, U. Ebert, R. FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 D-76275 Ettlingen Germany

ISBN: (纸本)9780819477873

Dual-band thermal imagers acquire information simultaneously in both the 8-12 μm (long-wave infrared, LWIR) and the 3-5 μm (mid-wave infrared, MWIR) spectral range. Compared to single-band thermal imagers they are expected to have several advantages in military applications. These advantages include the opportunity to use the best band for given atmospheric conditions (e. g. cold climate: LWIR, hot and humid climate: MWIR), the potential to better detect camouflaged targets and an improved discrimination between targets and decoys. Most of these advantages have not yet been verified and/or quantified. It is expected that image fusion allows better exploitation of the information content available with dual-band imagers especially with respect to detection of targets. We have developed a method for dual-band image fusion based on the apparent temperature differences in the two bands. This method showed promising results in laboratory tests. In order to evaluate its performance under operational conditions we conducted a field trial in an area with high thermal clutter. In such areas, targets are hardly to detect in single-band images because they vanish in the clutter structure. The image data collected in this field trial was used for a perception experiment. This perception experiment showed an enhanced target detection range and reduced false alarm rate for the fused images compared to the single-band images. © 2009 SPIE.

关键词： Image fusion

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PSInSAR: Detection of localized surface deformations with a modified StaMPS-algorithm

PSInSAR: Detection of localized surface deformations with a ...

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Image and Signal Processing for Remote Sensing XV

作者： Even, Markus Schunert, Alexander Schulz, Karsten Soergel, Uwe FGAN-Research Institute for Optronics and Pattern Recognition Ettlingen Germany Institute of Photogrammetrie and GeoInformation Leibniz Universität Hannover Germany

ISBN: (纸本)9780819477828

Persistent Scatterers Interferometric SAR (PSInSAR) is a powerful method for measuring surface deformations with millimeter-accuracy. Currently available algorithms are designed to detect large-scale earth movement or apply a predefined movement model. The analysis of the displacement of corner reflectors on our test area required the capability to detect localized deformation. To enable that, we modified StaMPS (Stanford Method for PS). We oppose the modified algorithm to the original algorithm, using time series of TerraSAR-X data from our test area. The finding is a distinct enhancement in the detection of localized deformation. © 2009 SPIE.

关键词： Interferometry

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Towards Euclidean reconstruction from video sequences

Towards Euclidean reconstruction from video sequences

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3rd International Conference on Computer Vision Theory and Applications

作者： Bulatov, Dimitri Research Institute for Optronics and Pattern Recognition Germany

ISBN: (纸本)9789898111210

This paper presents two algorithms needed to perform a dense 3D-reconstruction from video streams recorded with uncalibrated cameras. Our algorithm for camera self-calibration makes extensive use of the constant focal length. Furthermore, a fast dense reconstruction can be performed by fusion of tessellations obtained from different sub-sequences (LIFT). Moreover, we will present our system for performing the reconstruction in a projective coordinate system. Since critical motions are common in the majority of practical situations, care has been taken to recognize and deal with them.

关键词： calibration dense reconstruction Euclidean reconstruction

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Consideration of uncertainty in computer vision: Necessity and chance

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pattern recognition and Image Analysis 2008年第2期18卷 216-221页

作者： Meidow, J. Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

Observations and decisions in computer vision are inherently uncertain. The rigorous treatment of uncertainty has therefore received a lot of attention, since it not only improves the results compared to ad hoc methods but also makes the results more explainable. In this paper, the usefulness of stochastic approaches will be demonstrated by example with selected problems. These are given in the context of optimal estimation, self-diagnostics, and performance evaluation and cover all steps of the reasoning chain. The removal or interpretation of unexplainable thresholds and tuning parameters will be discussed for typical tasks in feature extraction, object reconstruction, and object classification. © 2008 Pleiades Publishing, Ltd.

关键词： Computer vision

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Metric reconstruction from video sequences

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pattern recognition and Image Analysis 2008年第2期18卷 300-308页

作者： Bulatov, D. FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

This paper is dedicated to modifying some steps needed to generate a dense 3D-reconstruction from a video stream. Since critical motions are common in the majority of practical situations, care was taken in our work to deal with some of these motions and "stitch" projective reconstructions from different coordinate systems. Moreover, the demand for real-time-near results in these applications is huge, so the system must be able to carry out a high-quality reconstruction in the shortest time. Finally, a new calibration algorithm will be presented and a hint will be given how a fast dense reconstruction can be obtained. © 2008 Pleiades Publishing, Ltd.

关键词： Image reconstruction

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Bayesian hypothesis generation and verification

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pattern recognition and Image Analysis 2008年第2期18卷 269-274页

作者： Armbruster, W. FGAN-FOM Research Institute for Optronics and Pattern Recognition Gutleuthausstr. 1 76275 Ettlingen Germany

Regarding computer vision as optimal decision making under uncertainty, a new optimization paradigm is introduced, namely, maximizing the product of the likelihood function and the posterior distribution on scene hypotheses given the results of feature extraction. Essentially this approach is a Bayesian formulation of hypothesis generation and verification. The approach is illustrated for model-based object recognition in range imagery, showing how segmentation results can optimally be incorporated into model matching. Several new match criteria for model based object recognition in range imagery are deduced from the theory. © 2008 Pleiades Publishing, Ltd.

关键词： Object recognition

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