Mr. Norbert Heinze Profile

Norbert Heinze

at Fraunhofer IOSB

SPIE Involvement:

Author

Publications (14)

Proceedings Article | 1 May 2017 Paper

Pilot study on real-time motion detection in UAS video data by human observer and image exploitation algorithm

Jutta Hild, Wolfgang Krüger, Stefan Brüstle, Patrick Trantelle, Gabriel Unmüßig, Michael Voit, Norbert Heinze, Elisabeth Peinsipp-Byma, Jürgen Beyerer

Proceedings Volume 10199, 1019903 (2017) https://doi.org/10.1117/12.2262477

KEYWORDS: Visualization, Target detection, Calibration, Eye, Video, Motion detection, Detection and tracking algorithms, Video surveillance, Motion analysis, Computing systems, Human-machine interfaces, Defense and security, Safety

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Proceedings Article | 13 May 2016 Paper

Interacting with target tracking algorithms in a gaze-enhanced motion video analysis system

Jutta Hild, Wolfgang Krüger, Norbert Heinze, Elisabeth Peinsipp-Byma, Jürgen Beyerer

Proceedings Volume 9841, 98410K (2016) https://doi.org/10.1117/12.2223726

KEYWORDS: Video, Detection and tracking algorithms, Motion analysis, Human-machine interfaces, Image processing algorithms and systems, Image segmentation, Visualization, Optical tracking, Motion detection, Switches

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Proceedings Article | 19 May 2015 Paper

Collaborative real-time motion video analysis by human observer and image exploitation algorithms

Jutta Hild, Wolfgang Krüger, Stefan Brüstle, Patrick Trantelle, Gabriel Unmüßig, Norbert Heinze, Elisabeth Peinsipp-Byma, Jürgen Beyerer

Proceedings Volume 9463, 94630C (2015) https://doi.org/10.1117/12.2180453

KEYWORDS: Video, Visualization, Eye, Optical tracking, Detection and tracking algorithms, Motion analysis, Tolerancing, Computing systems, Motion detection, Algorithm development

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Proceedings Article | 9 June 2014 Paper

Identification of spatially corresponding imagery using content-based image retrieval in the context of UAS video exploitation

Stefan Brüstle, Daniel Manger, Klaus Mück, Norbert Heinze

Proceedings Volume 9076, 907603 (2014) https://doi.org/10.1117/12.2054587

KEYWORDS: Image retrieval, Databases, Video, Visualization, Image filtering, Video surveillance, Content based image retrieval, Sensors, Artificial intelligence, Bismuth

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For many tasks in the fields of reconnaissance and surveillance it is important to know the spatial location represented by the imagery to be exploited. A task involving the assessment of changes, e.g. the appearance or disappearance of an object of interest at a certain location, can typically not be accomplished without spatial location information associated with the imagery. Often, such georeferenced imagery is stored in an archive enabling the user to query for the data with respect to its spatial location. Thus, the user is able to effectively find spatially corresponding imagery to be used for change detection tasks. In the field of exploitation of video taken from unmanned aerial systems (UAS), spatial location data is usually acquired using a GPS receiver, together with an INS device providing the sensor orientation, both integrated in the UAS. If during a flight valid GPS data becomes unavailable for a period of time, e.g. due to sensor malfunction, transmission problems or jamming, the imagery gathered during that time is not applicable for change detection tasks based merely on its georeference. Furthermore, GPS and INS inaccuracy together with a potentially poor knowledge of ground elevation can also render location information inapplicable. On the other hand, change detection tasks can be hard to accomplish even if imagery is well georeferenced as a result of occlusions within the imagery, due to e.g. clouds or fog, or image artefacts, due to e.g. transmission problems. In these cases a merely georeference based approach to find spatially corresponding imagery can also be inapplicable. In this paper, we present a search method based on the content of the images to find imagery spatially corresponding to given imagery independent from georeference quality. Using methods from content-based image retrieval, we build an image database which allows for querying even large imagery archives efficiently. We further evaluate the benefits of this method in the context of a video exploitation workflow on the basis of its integration into our video archive system.

Proceedings Article | 16 May 2013 Paper

Gaze interaction in UAS video exploitation

Jutta Hild, Stefan Brüstle, Norbert Heinze, Elisabeth Peinsipp-Byma

Proceedings Volume 8740, 87400H (2013) https://doi.org/10.1117/12.2015928

KEYWORDS: Video, Eye, Visualization, Image analysis, Sensors, Video surveillance, Databases, Image sensors, Visual analytics, Image resolution

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Proceedings Article | 22 June 2012 Paper

Archiving image sequences considering associated geographical and nongeographical attributes

Stefan Brüstle, Norbert Heinze

Proceedings Volume 8359, 83590Y (2012) https://doi.org/10.1117/12.919660

KEYWORDS: Databases, Sensors, Unmanned aerial vehicles, Image sensors, Video, Visualization, Data modeling, Image quality, Optical tracking, Data centers

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Proceedings Article | 5 May 2011 Paper

Detection and classification of moving objects from UAVs with optical sensors

Michael Teutsch, Wolfgang Krüger, Norbert Heinze

Proceedings Volume 8050, 80501J (2011) https://doi.org/10.1117/12.883102

KEYWORDS: Unmanned aerial vehicles, Target detection, Detection and tracking algorithms, Feature extraction, Video, Image sensors, Sensors, Image classification, Algorithm development, Image processing

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Proceedings Article | 26 April 2010 Paper

Image exploitation algorithms for reconnaissance and surveillance with UAV

N. Heinze, M. Esswein, W. Krüger, G. Saur

Proceedings Volume 7668, 76680U (2010) https://doi.org/10.1117/12.852555

KEYWORDS: Sensors, Video, Unmanned aerial vehicles, Image processing, Video surveillance, Image resolution, Super resolution, Algorithm development, Video processing, Image sensors

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Proceedings Article | 14 April 2008 Paper

Automatic image exploitation system for small UAVs

N. Heinze, M. Esswein, W. Krüger, G. Saur

Proceedings Volume 6946, 69460G (2008) https://doi.org/10.1117/12.782306

KEYWORDS: Video, Unmanned aerial vehicles, Sensors, Algorithm development, Video surveillance, Image processing, Video processing, Reconnaissance, Detection and tracking algorithms, Reconnaissance systems

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Proceedings Article | 7 May 2007 Paper

Image exploitation for MISAR

N. Heinze, M. Edrich, G. Saur, W. Krüger

Proceedings Volume 6568, 65680J (2007) https://doi.org/10.1117/12.720670

KEYWORDS: Synthetic aperture radar, Image processing, Sensors, Radar, Unmanned aerial vehicles, Image segmentation, Visualization, Image resolution, Reconnaissance, Image sensors

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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 | 5 September 2003 Paper

ATR-based camouflage effectiveness evaluation of MUSTAFA targets

Markus Mueller, Norbert Heinze, Dieter Clement

Proceedings Volume 5075, (2003) https://doi.org/10.1117/12.515356

KEYWORDS: Camouflage, Automatic target recognition, Target detection, Sensors, Detection and tracking algorithms, Infrared imaging, Infrared radiation, Reconnaissance, Image sensors, Forward looking infrared

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Proceedings Article | 18 September 2001 Paper

Multisensor data fusion and GIS utilization for ATR

Markus Mueller, Wolfgang Krueger, Norbert Heinze

Proceedings Volume 4370, (2001) https://doi.org/10.1117/12.440091

KEYWORDS: Image fusion, Data fusion, Geographic information systems, Detection and tracking algorithms, Sensors, Automatic target recognition, Target detection, Image registration, 3D modeling, Algorithm development

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Proceedings Article | 24 July 2000 Paper

Model-based target and background characterization

Markus Mueller, Wolfgang Krueger, Norbert Heinze

Proceedings Volume 4029, (2000) https://doi.org/10.1117/12.392515

KEYWORDS: Image fusion, Geographic information systems, Detection and tracking algorithms, Image registration, Algorithm development, Data modeling, Sensors, Target detection, Systems modeling, Synthetic aperture radar

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Showing 5 of 14 publications

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