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Optimal Camera Placement to measure Distances Conservativly Regarding Static and Dynamic Obstacles

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00005656
URN to cite this document: urn:nbn:de:bvb:703-epub-5656-9

Title data

Hänel, Maria L. ; Kuhn, Stefan ; Heinrich, Dominik ; Grüne, Lars ; Pannek, Jürgen:
Optimal Camera Placement to measure Distances Conservativly Regarding Static and Dynamic Obstacles.
Bayreuth , 2011

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Abstract

In modern production facilities industrial robots and humans are supposed to interact sharing a common working area. In order to avoid collisions, the distances between objects need to be measured conservatively which can be done by a camera network. To estimate the acquired distance, unmodelled objects, e.g., an interacting human, need to be modelled and distinguished from premodelled objects like workbenches or robots by image processing such as the background subtraction method. The quality of such an approach massively depends on the settings of the camera network, that is the positions and orientations of the individual cameras. Of particular interest in this context is the minimization of the error of the distance using the objects modelled by the background subtraction method instead of the real objects. Here, we show how this minimization can be formulated as an abstract optimization problem. Moreover, we state various aspects on the implementation as well as reasons for the selection of a suitable optimization method, analyze the complexity of the proposed method and present a basic version used for extensive experiments.

Further data

Item Type: Preprint, postprint
Additional notes (visible to public): erscheint in:
International Journal of Sensor Networks. Bd. 12 (2012) Heft 1 . - S. 25-36
DOI: https://doi.org/10.1504/IJSNET.2012.047713
DDC Subjects: 500 Science
500 Science > 510 Mathematics
Institutions of the University: Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics)
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics > Chair Mathematics V (Applied Mathematics) > Chair Mathematics V (Applied Mathematics) - Univ.-Prof. Dr. Lars Grüne
Profile Fields > Advanced Fields > Nonlinear Dynamics
Faculties
Faculties > Faculty of Mathematics, Physics und Computer Science
Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Mathematics
Profile Fields
Profile Fields > Advanced Fields
Language: English
Originates at UBT: Yes
URN: urn:nbn:de:bvb:703-epub-5656-9
Date Deposited: 31 May 2021 13:28
Last Modified: 08 Jun 2021 07:34
URI: https://epub.uni-bayreuth.de/id/eprint/5656

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