Detecting linear features by spatial point processes

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Chai, D.; Schmidt, A.; Heipke, C.: Detecting linear features by spatial point processes. In: International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 41 (2016), S. 841-848. DOI: http://dx.doi.org/10.5194/isprsarchives-XLI-B3-841-2016

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/700

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Sum total of downloads: 82




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Abstract: 
This paper proposes a novel approach for linear feature detection. The contribution is twofold: a novel model for spatial point processes and a new method for linear feature detection. It describes a linear feature as a string of points, represents all features in an image as a configuration of a spatial point process, and formulates feature detection as finding the optimal configuration of a spatial point process. Further, a prior term is proposed to favor straight linear configurations, and a data term is constructed to superpose the points on linear features. The proposed approach extracts straight linear features in a global framework. The paper reports ongoing work. As demonstrated in preliminary experiments, globally optimal linear features can be detected.
License of this version: CC BY 3.0
Document Type: article
Publishing status: publishedVersion
Issue Date: 2016
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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downloads by country:

pos. country downloads
total perc.
1 image of flag of Germany Germany 50 60.98%
2 image of flag of China China 10 12.20%
3 image of flag of United States United States 7 8.54%
4 image of flag of Mexico Mexico 2 2.44%
5 image of flag of France France 2 2.44%
6 image of flag of Canada Canada 2 2.44%
7 image of flag of Australia Australia 2 2.44%
8 image of flag of No geo information available No geo information available 1 1.22%
9 image of flag of Italy Italy 1 1.22%
10 image of flag of Brazil Brazil 1 1.22%
    other countries 4 4.88%

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