Femtosecond nonlinear single-photon photoelectric emission from tungsten at 248 nm

Girardeau-Montaut, J.P.; Girardeau-Montaut, Claire; Moustaizis, S.

doi:10.1088/0022-3727/27/4/026

Cited by 46 publications

(44 citation statements)

References 12 publications

(5 reference statements)

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“…where c states the number of the scanning object, o is the number of the operator, t represents the trial number and m c , o , t s , d , v , f is the mean point cloud distance between the reference and KinectFusion output in single trials defined by equation (3) 34…”

Section: Methodsmentioning

confidence: 99%

Comparison of depth cameras for three-dimensional reconstruction in medicine

Chiu

Thelwell

Senior

et al. 2019

Proc Inst Mech Eng H

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KinectFusion is a typical three-dimensional reconstruction technique which enables generation of individual three-dimensional human models from consumer depth cameras for understanding body shapes. The aim of this study was to compare three-dimensional reconstruction results obtained using KinectFusion from data collected with two different types of depth camera (time-of-flight and stereoscopic cameras) and compare these results with those of a commercial three-dimensional scanning system to determine which type of depth camera gives improved reconstruction. Torso mannequins and machined aluminium cylinders were used as the test objects for this study. Two depth cameras, Microsoft Kinect V2 and Intel Realsense D435, were selected as the representatives of time-of-flight and stereoscopic cameras, respectively, to capture scan data for the reconstruction of three-dimensional point clouds by KinectFusion techniques. The results showed that both time-of-flight and stereoscopic cameras, using the developed rotating camera rig, provided repeatable body scanning data with minimal operator-induced error. However, the time-of-flight camera generated more accurate three-dimensional point clouds than the stereoscopic sensor. Thus, this suggests that applications requiring the generation of accurate three-dimensional human models by KinectFusion techniques should consider using a time-of-flight camera, such as the Microsoft Kinect V2, as the image capturing sensor.

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Section: Methodsmentioning

confidence: 99%

Comparison of depth cameras for three-dimensional reconstruction in medicine

Chiu

Thelwell

Senior

et al. 2019

Proc Inst Mech Eng H

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“…To provide a quantitative evaluation we compared the reconstructed meshes with the very accurate point clouds measured by the Velodyne of the KITTI dataset through the CloudCompare tool [23]. This tool was used to compute the reconstruction error, i.e., the average of the distances between each Velodyne point and the nearest mesh triangle.…”

Section: Resultsmentioning

confidence: 99%

Incremental reconstruction of urban environments by Edge-Points Delaunay triangulation

Romanoni

Matteucci

2015

2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

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Urban reconstruction from a video captured by a surveying vehicle constitutes a core module of automated mapping. When computational power represents a limited resource and, a detailed map is not the primary goal, the reconstruction can be performed incrementally, from a monocular video, carving a 3D Delaunay triangulation of sparse points; this allows online incremental mapping for tasks such as traversability analysis or obstacle avoidance. To exploit the sharp edges of urban landscape, we propose to use a Delaunay triangulation of Edge-Points, which are the 3D points corresponding to image edges. These points constrain the edges of the 3D Delaunay triangulation to real-world edges. Besides the use of the Edge-Points, a second contribution of this paper is the Inverse Cone Heuristic that preemptively avoids the creation of artifacts in the reconstructed manifold surface. We force the reconstruction of a manifold surface since it makes it possible to apply computer graphics or photometric refinement algorithms to the output mesh. We evaluated our approach on four real sequences of the public available KITTI dataset by comparing the incremental reconstruction against Velodyne measurements.

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“…All points whose mean distances are bigger than (n) times of global standard deviation will then be considered as outliers and filtered out from point clouds, according to the assumption of Gaussian distribution . This technique of outlier removal can be computed by the open source software CloudCompare, which is stated as a plugin from the original source Point Cloud Library (PCL) …”

Section: The Proposed Methodsmentioning

confidence: 99%

New approach for monitoring historic and heritage buildings: Using terrestrial laser scanning and generalised Procrustes analysis

Jaafar

Meng

Sowter

et al. 2017

Struct Control Health Monit

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Summary Numerous different techniques and instruments can be used for structural monitoring with different requirements producing different results. For instance, some techniques need to use embedded sensors inside the building, such as geotechnical sensors. However, this method cannot be used for historic and heritage buildings. Other methods can offer high quality, but with a low point density and require fixed stations and targets, such as total stations. In such a case, the location of deformation tends to be known, such as dams, bridges, high‐rise buildings, and so forth. Nevertheless, this is not the case for historic and heritage buildings where each block could be subject to deformation. The challenge in such a case is to detect the deformation without any previous knowledge. The aim of this research is to develop a new approach to detect and localise unpredictable deformation. It is based on terrestrial laser scanner measurements and generalised Procrustes analysis techniques to determine deformation vectors, although boxing structure and F‐tests are used to detect and localise deformation. In summary, after applying this approach, the whole concerned building is represented as parts, for each of them, the displacement vector and deformation probability are estimated. Validation experiments have shown the capability of the proposed method to detect and localise deformation with magnitude less than noise level in simulated data and of subcentimetre level for ranges up to 10 m in real scan data. Finally, the new approach has been applied to an English Historic site, Bellmanpark Limeklins.

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Femtosecond nonlinear single-photon photoelectric emission from tungsten at 248 nm

Cited by 46 publications

References 12 publications

Comparison of depth cameras for three-dimensional reconstruction in medicine

Comparison of depth cameras for three-dimensional reconstruction in medicine

Incremental reconstruction of urban environments by Edge-Points Delaunay triangulation

New approach for monitoring historic and heritage buildings: Using terrestrial laser scanning and generalised Procrustes analysis

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