Three-dimensional obstacle classification in laser range data

Armbruster, Walter; Bers, Karl-Heinz

doi:10.1117/12.328046

Cited by 3 publications

(3 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, the IR data are flawed because of lens distortions that were not taken into account yet. To give qualitative error estimations for the proposed methods, sophisticated ATR procedures [1] were used to track a chosen vehicle from the test arrangement. We chose a truck that was visible in the FOV of IR camera and laser scanner throughout the whole recording process.…”

Section: Discussionmentioning

confidence: 99%

“…Beside the investigation of automatic target recognition and classification procedures for the output of single sensors like laser radar [1] or IR cameras [4], a lot of research work at the FOM is done in the field of multisensorial data fusion. Subject to analysis are mobile sensors on a common platform as well as distributed systems.…”

Section: Data Processingmentioning

confidence: 99%

“…Black areas within the image are points outside the camera's FOV or regions where no information is available due to shadow effects or obscuration. Objects standing out from the ground level can be classified as obstacles [1] in order to represent them separately and provide them with the respective IR texture (Figure 10b). Additionally, this allows producing views of the objects from different aspects.…”

Section: )mentioning

confidence: 99%

See 2 more Smart Citations

Imaging sensor fusion and enhanced vision for helicopter landing operations

2006

View full text Add to dashboard Cite

An automatic target recognition system has been assembled and tested at the Research Institute for Optronics and Pattern Recognition in Germany over the last years. Its multisensorial design comprises off-the-shelf components: an FPA infrared camera, a scanning laser radar und an inertial measurement unit. In the paper we describe several possibilities for the use of this multisensor equipment during helicopter missions. We discuss suitable data processing methods, for instance the automatic time synchronization of different imaging sensors, the pixel-based data fusion and the incorporation of collateral information. The results are visualized in an appropriate way to present them on a cockpit display. We also show how our system can act as a landing aid for pilots within brownout conditions (dust clouds caused by the landing helicopter).

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Data Processingmentioning

confidence: 99%

Section: )mentioning

confidence: 99%

See 1 more Smart Citation

Imaging sensor fusion and enhanced vision for helicopter landing operations

2006

View full text Add to dashboard Cite

show abstract

On the scattering mechanism of power lines at millimeter-waves

Essen

Boehmsdorff

Biegel

et al. 2002

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

The radar signature of power lines is of high importance in the design of systems for helicopter collision avoidance. Laboratory measurements have been reported previously, but field measurements at millimeter waves are missing. The present contribution describes measurements done in ground-based configuration with a real aperture scanning-beam radar operating simultaneously at 35 and 94 GHz. By scanning, an aspect angle interval of 60° was covered, including the broadside aspect. The narrow beam width allowed to discriminate between different wires separated horizontally. While these measurements were done under a very shallow incidence angle, assisting measurements were done with the same radar mounted into an aircraft using synthetic aperture radar techniques. The results for shallow and steep incidence are compared and show the significant influence of this parameter on the signature of the power line. Additionally the measurement results are compared with those from model calculations

show abstract