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Change detection of mobile Lidar data using cloud computing

Liu, K; Boehm, J; Alis, C; (2016) Change detection of mobile Lidar data using cloud computing. In: Proceedings of the XXIII ISPRS Congress. (pp. pp. 309-313). International Society of Photogrammetry and Remote Sensing (ISPRS): Prague, Czech Republic. Green open access

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Abstract

Change detection has long been a challenging problem although a lot of research has been conducted in different fields such as remote sensing and photogrammetry, computer vision, and robotics. In this paper, we blend voxel grid and Apache Spark together to propose an efficient method to address the problem in the context of big data. Voxel grid is a regular geometry representation consisting of the voxels with the same size, which fairly suites parallel computation. Apache Spark is a popular distributed parallel computing platform which allows fault tolerance and memory cache. These features can significantly enhance the performance of Apache Spark and results in an efficient and robust implementation. In our experiments, both synthetic and real point cloud data are employed to demonstrate the quality of our method.

Type: Proceedings paper
Title: Change detection of mobile Lidar data using cloud computing
Event: XXIII ISPRS Congress
Location: Prague, Czech Republic
Dates: 12 July 2016 - 19 July 2016
Open access status: An open access version is available from UCL Discovery
DOI: 10.5194/isprsarchives-XLI-B3-309-2016
Publisher version: http://dx.doi.org/10.5194/isprs-archives-XLI-B3-30...
Language: English
Additional information: All site content, except where otherwise noted, is licensed under the Creative Commons Attribution 3.0 License.
Keywords: Point Cloud, Cloud Computing, Change Detection, Mobile Mapping, LiDAR
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng
URI: https://discovery.ucl.ac.uk/id/eprint/1539073
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