Occlusion Detection with Edge Extraction Algorithm in Terrestrial Laser Scanner Point Cloud Data

Heidarimozaffar, Morteza; Masoud, Varshousaz; Saadatseresht, M.

doi:10.29252/jgit.3.1.27

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2016

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“…Another example is that developed by Heidari Mozaffar et al. () where edges detected on a range image are used to define occlusions in the point cloud acquired with a TLS. A location around the object is selected as the NBV from which the maximum number of points in the occluded areas is visible.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Placement of a Terrestrial Laser Scanner with an Emphasis on Reducing Occlusions

Heidarimozaffar

Varshosaz

2016

The Photogrammetric Record

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In this paper, a new automated algorithm is proposed that finds the optimum locations of a terrestrial laser scanner (TLS), ensuring completeness of data and minimising the number of scanning locations. The process starts with an initial scan and placing a 3D grid of candidate stations over the entire scan area. A global visibility analysis is then performed to identify the next best view (NBV) location. The TLS is placed on this selected point and a new scan is recorded. Having updated the initial scan with the resulting point cloud, the model is checked for completeness and density. The process is repeated until full coverage of the scan area is achieved by determining the best global arrangement with the minimum number of stations. Experiments show that the algorithm is able to automatically determine the station positions and provide a coverage of 99Á5% for simulated data and 91% for real data.

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Section: Literature Reviewmentioning

confidence: 99%