Dr. Dieter N. Willersinn Profile

Dr. Dieter N. Willersinn

Head of Assessment and Situation Awareness at Fraunhofer IOSB

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Publications (18)

Proceedings Article | 13 March 2018 Paper

Distant pulse oximetry based on skin region extraction and multi-spectral measurement

Christian Herrmann, Jürgen Metzler, Dieter Willersinn, Jürgen Beyerer

Proceedings Volume 10576, 105762O (2018) https://doi.org/10.1117/12.2293623

KEYWORDS: Image segmentation, Sensors, Oximetry, Heart, Optical filters, Cameras, Skin, Oxygen, Signal to noise ratio, RGB color model, Convolutional neural networks

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Proceedings Article | 3 March 2017 Paper

Automatic detection of measurement points for non-contact vibrometer-based diagnosis of cardiac arrhythmias

Jürgen Metzler, Kristian Kroschel, Dieter Willersinn

Proceedings Volume 10135, 101351S (2017) https://doi.org/10.1117/12.2253654

KEYWORDS: Chest, Electronic filtering, Skin, 3D metrology, Cameras, Neck, Emergency medicine, Heart, Electrocardiography, Electrodes, Adhesives, Diagnostics, Vibrometry, Arteries

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Proceedings Article | 21 October 2016 Paper

Real-time person detection in low-resolution thermal infrared imagery with MSER and CNNs

Christian Herrmann, Thomas Müller, Dieter Willersinn, Jürgen Beyerer

Proceedings Volume 9987, 99870I (2016) https://doi.org/10.1117/12.2240940

KEYWORDS: Detection and tracking algorithms, Long wavelength infrared, Cameras, Infrared imaging, Thermography, Infrared radiation, Infrared detectors, Sensors, Network architectures, Surveillance

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In many camera-based systems, person detection and localization is an important step for safety and security applications such as search and rescue, reconnaissance, surveillance, or driver assistance. Long-wave infrared (LWIR) imagery promises to simplify this task because it is less affected by background clutter or illumination changes. In contrast to a lot of related work, we make no assumptions about any movement of persons or the camera, i.e. persons may stand still and the camera may move or any combination thereof. Furthermore, persons may appear arbitrarily in near or far distances to the camera leading to low-resolution persons in far distances. To address this task, we propose a two-stage system, including a proposal generation method and a classifier to verify, if the detected proposals really are persons. In contradiction to use all possible proposals as with sliding window approaches, we apply Maximally Stable Extremal Regions (MSER) and classify the detected proposals afterwards with a Convolutional Neural Network (CNN). The MSER algorithm acts as a hot spot detector when applied to LWIR imagery. Because the body temperature of persons is usually higher than the background, they appear as hot spots in the image. However, the MSER algorithm is unable to distinguish between different kinds of hot spots. Thus, all further LWIR sources such as windows, animals or vehicles will be detected, too. Still by applying MSER, the number of proposals is reduced significantly in comparison to a sliding window approach which allows employing the high discriminative capabilities of deep neural networks classifiers that were recently shown in several applications such as face recognition or image content classification. We suggest using a CNN as classifier for the detected hot spots and train it to discriminate between person hot spots and all further hot spots. We specifically design a CNN that is suitable for the low-resolution person hot spots that are common with LWIR imagery applications and is capable of fast classification. Evaluation on several different LWIR person detection datasets shows an error rate reduction of up to 80 percent compared to previous approaches consisting of MSER, local image descriptors and a standard classifier such as an SVM or boosted decision trees. Further time measurements show that the proposed processing chain is capable of real-time person detection in LWIR camera streams.

Proceedings Article | 18 December 2012 Paper

Towards video processing in vehicles under adverse weather conditions

Michael Grinberg, Nick Schneider, Frank Pagel, Daniel Manger, Dieter Willersinn

Proceedings Volume 8550, 855020 (2012) https://doi.org/10.1117/12.999343

KEYWORDS: Visibility, Image restoration, Video processing, Visibility through fog, Visualization, Cameras, Image processing, Information visualization, Fiber optic gyroscopes, Video

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Proceedings Article | 19 November 2012 Paper

Semi-automatic people counting in aerial images of large crowds

Christian Herrmann, Juergen Metzler, Dieter Willersinn

Proceedings Volume 8542, 85420Q (2012) https://doi.org/10.1117/12.974657

KEYWORDS: Image segmentation, Video surveillance, Video, Systems modeling, Data modeling, Time metrology, Image processing, Cameras, Image analysis, Imaging systems

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Proceedings Article | 28 April 2010 Paper

Video-tracker trajectory analysis: who meets whom, when and where

U. Jäger, D. Willersinn

Proceedings Volume 7709, 77090U (2010) https://doi.org/10.1117/12.850054

KEYWORDS: Video, Video surveillance, Video processing, Kinematics, Optical inspection, Weapons, Environmental sensing, Homeland security, Image retrieval, Optical tracking

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Proceedings Article | 22 April 2010 Paper

Performance evaluation of FIR sensor systems applied to pedestrian detection

S. Franz, R. Schweiger, O. Loehlein, D. Willersinn, K. Kroschel

Proceedings Volume 7662, 766217 (2010) https://doi.org/10.1117/12.850150

KEYWORDS: Sensors, Databases, Sensor performance, Roads, Data acquisition, Environmental sensing, Calibration, Night vision systems, Image sensors, Far infrared

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Proceedings Article | 15 April 2010 Paper

Human detection in MOUT scenarios using covariance descriptors and supervised manifold learning

Jürgen Metzler, Dieter Willersinn

Proceedings Volume 7701, 770106 (2010) https://doi.org/10.1117/12.850213

KEYWORDS: Matrices, Principal component analysis, Feature extraction, Sensors, Vector spaces, Machine learning, Cameras, Image processing, Threat warning systems, Image segmentation

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Proceedings Article | 18 January 2010 Paper

Assessment of image sensor performance with statistical perception performance analysis

Stefan Franz, Dieter Willersinn, Kristian Kroschel

Proceedings Volume 7539, 75390I (2010) https://doi.org/10.1117/12.838969

KEYWORDS: Sensors, Modulation transfer functions, Signal to noise ratio, Imaging systems, Sensor performance, Lenses, Roads, Cameras, Spatial frequencies, Data processing

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Proceedings Article | 5 May 2009 Paper

On the airworthiness approval of a SAR ATR system

Dieter Willersinn, Uwe Jäger, Herbert Schlatt, Christoph Stahl

Proceedings Volume 7335, 73350K (2009) https://doi.org/10.1117/12.820133

KEYWORDS: Automatic target recognition, Safety, Synthetic aperture radar, Global Positioning System, Navigation systems, Hazard analysis, Satellites, Fermium, Frequency modulation, Weapons

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Proceedings Article | 28 April 2009 Paper

Robust tracking of people in crowds with covariance descriptors

Jürgen Metzler, Dieter Willersinn

Proceedings Volume 7341, 73410T (2009) https://doi.org/10.1117/12.820067

KEYWORDS: Matrices, Mahalanobis distance, RGB color model, Situational awareness sensors, Unmanned aerial vehicles, Error control coding, Data processing, Automatic tracking, Video, Distance measurement

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Proceedings Article | 7 October 2008 Paper

Multisensor benchmark data for riot control

Uwe Jäger, Marc Höpken, Bernhard Dürr, Jürgen Metzler, Dieter Willersinn

Proceedings Volume 7114, 711403 (2008) https://doi.org/10.1117/12.799822

KEYWORDS: Sensors, Software development, Detection and tracking algorithms, Video, Algorithm development, Data acquisition, Video surveillance, Cameras, Error control coding, Quality measurement

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Proceedings Article | 7 October 2008 Paper

Assessment and optimization of methods for tracking people in riot control scenarios

Yvonne Hübner, Jürgen Metzler, Bernhard Dürr, Uwe Jäger, Dieter Willersinn

Proceedings Volume 7114, 711404 (2008) https://doi.org/10.1117/12.799827

KEYWORDS: Error control coding, Detection and tracking algorithms, Sensors, Data processing, Data acquisition, Control systems, Situational awareness sensors, Information security, Cameras, Unmanned aerial vehicles

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Proceedings Article | 7 May 2007 Paper

Toward a sensor-based threat warning system for patrols in MOUT scenarios

Jürgen Metzler, Dieter Willersinn

Proceedings Volume 6566, 65660T (2007) https://doi.org/10.1117/12.721314

KEYWORDS: Sensors, Threat warning systems, Head, Cameras, Intelligence systems, Detection and tracking algorithms, Roads, Weapons, Data processing, Video

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Proceedings Article | 21 September 2004 Paper

IR and SAR automatic target detection benchmarks

Uwe Jaeger, Helmut Maier-Herburger, Christoph Stahl, Norbert Heinze, Dieter Willersinn

Proceedings Volume 5426, (2004) https://doi.org/10.1117/12.542102

KEYWORDS: Automatic target recognition, Algorithm development, Synthetic aperture radar, Detection and tracking algorithms, Fourier transforms, Target detection, Infrared imaging, Standards development, Infrared sensors, Defense technologies

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Proceedings Article | 22 October 2001 Paper

Performance prediction of vehicle detection algorithms

P. Klausmann, Kristian Kroschel, Dieter Willersinn

Proceedings Volume 4379, (2001) https://doi.org/10.1117/12.445385

KEYWORDS: Detection and tracking algorithms, Data modeling, Performance modeling, Image quality, Algorithm development, Target detection, Visual process modeling, Infrared imaging, Infrared radiation, Thermal modeling

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Proceedings Article | 24 August 1999 Paper

Assessment of machine-assisted target detection

P. Klausmann, E. Peinspipp-Byma, Wolfgang Roller, Gunter Saur, Dieter Willersinn

Proceedings Volume 3718, (1999) https://doi.org/10.1117/12.359979

KEYWORDS: Detection and tracking algorithms, Image processing, Image analysis, Target detection, Image quality, Automatic target recognition, Visualization, Computing systems, Algorithm development, Ions

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Proceedings Article | 24 August 1999 Paper

Evaluation framework for ATR algorithms

Stefan Fries, P. Klausmann, U. Jaeger, Gunter Saur, Dieter Willersinn, G. Hofele, Ulrich Thoennessen

Proceedings Volume 3718, (1999) https://doi.org/10.1117/12.359980

KEYWORDS: Algorithm development, Detection and tracking algorithms, Image processing, Image sensors, Sensors, Data acquisition, Software development, Human-machine interfaces, Automatic target recognition, Distance measurement

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Showing 5 of 18 publications

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