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Hinks, Tommy
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Hinks, Tommy
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Hinks, Tommy
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Now showing 1 - 5 of 5
- PublicationNew possibilities for damage prediction from tunnel subsidence using aerial LiDAR data(2010-06)
; ; Computation modelling has not been fully exploited for predicting building damage due to tunnel-induced subsidence, because of the expense and time required to create computational meshes for the vast quantity of buildings that may be impacted along a tunnel’s route. A possible circumvention of such a resource commitment lies in the exploitation of remote sensing data in the form of aerial laser scans (also know as Light Detection and Ranging – LiDAR). This paper presents work accomplished to date in the creation of a pipeline to automate the conversion of aerial LiDAR point cloud data directly into Finite Element Method (FEM) meshes without the intermediary step of triangulation-based conversion or reliance on geometric primitives through a Computer Aided Design (CAD) program. The paper highlights recent advances in flight path planning, data processing, plane identification, wall segmentation, and data transformation.1399 - PublicationPoint Cloud Data Conversion into Solid Models via Point-Based Voxelization(American Society of Civil Engineers, 2013-05)
; ; ; Automated conversion of point cloud data from laser scanning into formats appropriate for structural engineering holds great promise for exploiting increasingly available aerially and terrestrially based pixelized data for a wide range of surveying-related applications from environmental modeling to disaster management. This paper introduces a point-based voxelization method to automatically transform point cloud data into solid models for computational modeling. The fundamental viability of the technique is visually demonstrated for both aerial and terrestrial data. For aerial and terrestrial data, this was achieved in less than 30 s for data sets up to 650,000 points. In all cases, the solid models converged without any user intervention when processed in a commercial finite-element method program.3074Scopus© Citations 80 - PublicationFlying Voxel Method with Delaunay Triangulation Criterion for Façade/Feature Detection for Computation(American Society of Civil Engineers, 2012-11)
; ; ; A new algorithm is introduced to directly reconstruct geometric models of building façades from terrestrial laser scanning data without using either manual intervention or a third-party, computer-aided design (CAD) package. The algorithm detects building boundaries and features and converts the point cloud data into a solid model appropriate for computational modeling. The algorithm combines a voxel-based technique with a Delaunay triangulation–based criterion. In the first phase, the algorithm detects boundary points of the façade and its features from the raw data. Subsequently, the algorithm determines whether holes are actual openings or data deficits caused by occlusions and then fills unrealistic openings. The algorithm’s second phase creates a solid model using voxels in an octree representation. The algorithm was applied to the façades of three masonry buildings, successfully detected all openings, and correctly reconstructed the façade boundaries. Geometric validation of the models against measured drawings showed overall dimensions correct to 1.2%, most opening areas to 3%, and simulation results within 5% of those predicted by CAD-based models.2274Scopus© Citations 43 - PublicationFlight optimization algorithms for aerial LiDAR capture for urban infrastructure model generation(American Society of Civil Engineering (ASCE), 2009-11)
; ; Aerial Light Detection and Ranging (LiDAR) offers the potential to auto-generate detailed, three-dimensional (3D) models of the built environment in urban settings. Auto-generation is needed as manual generation is not economically feasible for large areas, and yet such models would offer distinct advantages for a wide range of applications from improved noise and pollution prediction to disaster mitigation modeling. Current technology and the dense geometry of urban environments are two major constraints in LiDAR scanning. This paper outlines the difficulties related to effective vertical surface data capture in an urban environment for the purpose of 3D visualization. Further, the traditional point data captured with LiDAR scans is unsuitable for visualization. Therefore, surface reconstruction algorithms must be applied to the data. These algorithms are largely dependent on the uniformity of the resolution in the point data. Principles for geometric optimization of data capture on vertical surfaces, thereby improving resolution uniformity, are presented.2282Scopus© Citations 45 - PublicationVisualisation of urban airborne laser scanning data with occlusion imagesAirborne Laser Scanning (ALS) was introduced to provide rapid, high resolution scans of landforms for computational processing. More recently, ALS has been adapted for scanning urban areas. The greater complexity of urban scenes necessitates the development of novel methods to exploit urban ALS to best advantage. This paper presents occlusion images: a novel technique that exploits the geometric complexity of the urban environment to improve visualisation of small details for better feature recognition. The algorithm is based on an inversion of traditional occlusion techniques.
367Scopus© Citations 13