Handling Occlusions for Accurate 3D Urban Cartography: A New Approach Based on Characterization and Multiple Passages

Aijazi, Ahmad Kamal; Checchin, Paul; Trassoudaine, Laurent

doi:10.1109/3dimpvt.2012.26

Cited by 2 publications

(2 citation statements)

References 11 publications

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“…In such a non-structured environment, the clustering/segmentation task, especially if only based on 3D information, can be quite difficult. This type of 3D data is widely hampered due to jump edges [38], feature occlusions [39], varying point resolution [40], close objects of large dimensions, and measurement noise [40], etc. For these reasons, a more robust method of modified fuzzy C-means clustering is employed in this work.…”

Section: Fuzzy C-means Clusteringmentioning

confidence: 99%

Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System

Aijazi

Laurent

Trassoudaine

et al. 2019

Sensors

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Automatic and accurate mapping and modeling of underground infrastructure has become indispensable for several important tasks ranging from urban planning and construction to safety and hazard mitigation. However, this offers several technical and operational challenges. The aim of this work is to develop a portable automated mapping solution for the 3D mapping and modeling of underground pipe networks during renovation and installation work when the infrastructure is being laid down in open trenches. The system is used to scan the trench and then the 3D scans obtained from the system are registered together to form a 3D point cloud of the trench containing the pipe network using a modified global ICP (iterative closest point) method. In the 3D point cloud, pipe-like structures are segmented using fuzzy C-means clustering and then modeled using a nested MSAC (M-estimator SAmpling Consensus) algorithm. The proposed method is evaluated on real data pertaining to three different sites, containing several different types of pipes. We report an overall registration error of less than 7 % , an overall segmentation accuracy of 85 % and an overall modeling error of less than 5 % . The evaluated results not only demonstrate the efficacy but also the suitability of the proposed solution.

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Section: Fuzzy C-means Clusteringmentioning

confidence: 99%

Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System

Aijazi

Laurent

Trassoudaine

et al. 2019

Sensors

Self Cite

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“…The 3D models have been widely used in various applications such as virtual cultural heritage conservation [1], architecture design [2], and cartography [3]. The virtual cultural heritage conservation refers to 3D digitization and replication of cultural heritage, which has become an interesting and challenging research field [4].…”

Section: Introductionmentioning

confidence: 99%

Automated 3D Scenes Reconstruction Using Multiple Stereo Pairs from Portable Four-Camera Photographic Measurement System

Peng

Zhang

et al. 2015

International Journal of Optics

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An effective automatic 3D reconstruction method using a portable four-camera photographic measurement system (PFCPMS) is proposed. By taking advantage of the complementary stereo information from four cameras, a fast and highly accurate feature point matching algorithm is developed for 3D reconstruction. Specifically, we first utilize a projection method to obtain a large number of dense feature points. And then a reduction and clustering treatment is applied to simplify the Delaunay triangulation process and reconstruct a 3D model for each scene. In addition, a 3D model stitching approach is proposed to further improve the performance of the limited field-of-view for image-based method. The experimental results tested on the 172 cave in Mogao Grottoes indicate that the proposed method is effective to reconstruct a 3D scene with a low-cost four-camera photographic measurement system.

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Handling Occlusions for Accurate 3D Urban Cartography: A New Approach Based on Characterization and Multiple Passages

Cited by 2 publications

References 11 publications

Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System

Automatic Detection and Modeling of Underground Pipes Using a Portable 3D LiDAR System

Automated 3D Scenes Reconstruction Using Multiple Stereo Pairs from Portable Four-Camera Photographic Measurement System

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