We are now gradually entering the era of big data - maybe a bit too much of a buzzword, but it is not lied. Technology is evolving fast, enabling faster and more efficient data acquisition, storage, retrieval and processing. Point cloud datasets are such a type which relies on la
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We are now gradually entering the era of big data - maybe a bit too much of a buzzword, but it is not lied. Technology is evolving fast, enabling faster and more efficient data acquisition, storage, retrieval and processing. Point cloud datasets are such a type which relies on large files and lots of processing power. The rather fast evolutions in technology enable the shared idea between Delft University of Technology and Fugro of an ‘Open Point Cloud Map’. This Open Point Cloud Map aims at making point cloud datasets easily available to the public, even letting them performsimple analysis. Both Fugro and TU Delft want to take lead in development of such an environment; three student teams from TU Delft thus form a partnership with Fugro to kick-off three in-depth researches which would result in one step closer to the vision of OPCM. The ChronoCity team will focus on the time-component (Figure 1.1) in the acquainted point clouds, while the other two teams focus on location-dependency and different scales and granularities of the datasets.
The Chronocity-team strives to create an online interactive tool which gives the user the ability to view, explore and analyze massive point cloud datasets on-the-fly. Since the limited timespan in which the project should take place this would not yield a fully optimized application, but at least the general principles are defined and evaluated on for a more defined future in the development of the OPCM. A large portion of the efforts will go into making the data and analyses available to the public - in an interactive and user-friendly way; because without this availability, the underlying principles are not brought to the public also. Regarding these underlying principles the most important one is change detection. During the project a suitable algorithm is designed and evaluated for detecting new, removed and changed geometric points.