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63-4: A Novel Real-Time Full-Color 3d Holographic (diffractive) Video Capture, processing, and Transmission Pipeline Using Off-the-Shelf Hardware

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SId Symposium digest of Technical Papers 2022年第1期53卷

作者： Ankur Samanta Gregor Mackenzie Tyler Rathkamp Adrian Cable darran Milne Andrzej Kaczorowski Ronjon Nag R42 Institute Palo Alto CA USA VividQ Cambridge UK

This paper details the world's first live 3d holographic (diffractive) video call using off-the-shelf hardware. We introduce a novel pipeline that facilitates the capture, processing, and transmission of RGBZ data... 详细信息

关键词： Holography 3d displays Augmented Reality 3d data Capture 3d data processing 3d data Transmission

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Uniformizing Techniques to Process CT Scans with 3d CNNs for Tuberculosis Prediction 1

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3rd International Workshop on Predictive Intelligence in Medicine (PRIME)

作者： Zunair, Hasib Rahman, Aimon Mohammed, Nabeel Cohen, Joseph Paul Concordia Univ Montreal PQ Canada North South Univ Dhaka Bangladesh Univ Montreal Mila Montreal PQ Canada

ISBN: (数字)9783030593544

ISBN: (纸本)9783030593537;9783030593544

A common approach to medical image analysis on volumetric data uses deep 2d convolutional neural networks (CNNs). This is largely attributed to the challenges imposed by the nature of the 3d data: variable volume size, GPU exhaustion during optimization. However, dealing with the individual slices independently in 2d CNNs deliberately discards the depth information which results in poor performance for the intended task. Therefore, it is important to develop methods that not only overcome the heavy memory and computation requirements but also leverage the 3d information. To this end, we evaluate a set of volume uniformizing methods to address the aforementioned issues. The first method involves sampling information evenly from a subset of the volume. Another method exploits the full geometry of the 3d volume by interpolating over the z-axis. We demonstrate performance improvements using controlled ablation studies as well as put this approach to the test on the ImageCLEF Tuberculosis Severity Assessment 2019 benchmark. We report 73% area under curve (AUC) and binary classification accuracy (ACC) of 67.5% on the test set beating all methods which leveraged only image information (without using clinical meta-data) achieving 5th position overall. All codes and models are made available at https:// ***/hasibzunair/uniformizing- 3d.

关键词： 3d data processing CT images Convolutional neural networks

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An appraisal of the geometry and energy efficiency of parabolic trough collectors with laser scanners and image processing

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RENEWABLE ENERGY 2019年 134卷 64-77页

作者： Salamanca, Santiago Merchan, Pilar Adan, Antonio Perez, Emiliano Univ Extremadura Escuela Ingn Ind Avda Elvas S-N Badajoz 06006 Spain Univ Castilla La Mancha Escuela Super Informat Paseo Univ 4 E-13071 Ciudad Real Spain

This paper presents an original method for the analysis of the geometric and optical properties of parabolic solar trough collectors using laser scanners and image processing techniques. The aim of the paper is to propose a methodology with which to automatically analyse geometric errors in the mirror and receiver, in addition to presenting an empirical assessment of one of the most important factors that determines the entire energy efficiency of solar plants, which is optical efficiency. The definition of canonical images has allowed us to characterise a set of parameters that evaluates errors on both the surface of the parabolic reflector and regarding the orientation of the receiver. In this framework, energy efficiency is established in terms of two parameters, denominated as the interception index and the concentration index. The proposed method has been tested on-site on real surfaces of parabolic solar trough collectors in an operating solar thermal plant. The results obtained are sufficiently accurate and reliable to be able to recommend that researchers and plants reproduce this method in this kind of installations. (C) 2018 Elsevier Ltd. All rights reserved.

关键词： Parabolic solar trough collectors Solar thermal power plants Laser scanners 3d data processing 3d surfaces

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PolyProc: A Modular processing Pipeline for X-ray diffraction Tomography

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INTEGRATING MATERIALS ANd MANUFACTURING INNOVATION 2019年第3期8卷 388-399页

作者： Kang, Jiwoong Lu, Ning Loo, Issac Senabulya, Nancy Shahani, Ashwin J. Univ Michigan Dept Chem Engn Ann Arbor MI 48109 USA Univ Michigan Dept Mat Sci & Engn Ann Arbor MI 48109 USA Univ Michigan Dept Ind & Operat Engn Ann Arbor MI 48109 USA Univ Michigan Michigan Ctr Mat Characterizat Ann Arbor MI 48109 USA

direct imaging of three-dimensional microstructure via X-ray diffraction-based techniques gives valuable insight into the crystallographic features that influence materials properties and performance. For instance, X-ray diffraction tomography provides information on grain orientation, position, size, and shape in a bulk specimen. As such techniques become more accessible to researchers, demands are placed on processing the datasets that are inherently "noisy," multi-dimensional, and multimodal. To fulfill this need, we have developed a one-of-a-kind function package, PolyProc, that is compatible with a range of data shapes, from planar sections to time-evolving and three-dimensional orientation data. Our package comprises functions to import, filter, analyze, and visualize the reconstructed grain maps. To accelerate the computations in our pipeline, we harness computationally efficient approaches: for instance, data alignment is done via genetic optimization;grain tracking through the Hungarian method;and feature-to-feature correlation through k-nearest neighbors algorithm. As a proof-of-concept, we test our approach in characterizing the grain texture, topology, and evolution in a polycrystalline Al-Cu alloy undergoing coarsening.

关键词： 3d data processing X-ray diffraction contrast tomography Grain mapping Microstructure evolution

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3d-FLARE: A Touchless Full-3d Fingerprint Recognition System Based on Laser Sensing

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IEEE ACCESS 2020年 8卷 145513-145534页

作者： Galbally, Javier Beslay, Laurent Bostrom, Gunnar European Commiss DG Joint Res Ctr I-21027 Ispra Italy

"The friction ridge pattern is a 3d structure which, in its natural state, is not deformed by contact with a surface". Building upon this rather trivial observation, the present work constitutes a first solid step towards a paradigm shift in fingerprint recognition from its very foundations. We explore and evaluate the feasibility to move from current technology operating on 2d images of elastically deformed impressions of the ridge pattern, to a new generation of systems based on full-3d models of the natural non-deformed ridge pattern itself. There are already a small number of previous studies that have already started scratching the surface of 3d fingerprint recognition and that should not go overlooked. However, the vast majority of these few successful approaches published so far, are based on the reconstruction of fingerprints from multiple 2d images acquired with different lighting conditions (photometric stereo 3d reconstruction) or acquired from different angles (stereo vision 3d reconstruction). Such reconstruction methods lead in general to 2d fingerprints wrapped over the overall volume of the finger. These volumetric fingerprints have shown some promising performance, but still miss the real depth information of the ridge pattern, which, in the best case scenario, is coarsely estimated during the error-prone reconstruction process. In the present work we take one step further, directly acquiring for the first time in a consistent and repeatable manner, full-3d fingerprint models stored as point-clouds, where each point is defined by its [x,y,z] coordinates. This way, the 3d data is directly measured by the sensor, with no post-processing reconstruction stage required. The complete recognition system developed represents as well an alternative to traditional technology based on minutiae detection. It shows that image-based processing algorithms and descriptors can be successfully applied to the new full-3d data, reaching very competitive results and con

关键词： Three-dimensional displays Two dimensional displays Solid modeling Friction Biometrics (access control) Reliability Sensors 3d data processing fingerprint recognition laser sensing

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3d data processing: Towards the Automated BIM in Inhabited Indoors

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REVISTA IBEROAMERICANA dE AUTOMATICA E INFORMATICA INdUSTRIAL 2011年第4期8卷 357-370页

作者： Adan, A. Huber, d. Univ Castilla La Mancha Dept Ingn Elect Elect & Automat E-13071 Ciudad Real Spain Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA

In this paper we present a method for the reconstruction of interiors using a set of panoramic range data in scenes with clutter and occlusion. Although the ultimate goal of our project is to obtain automated Building Information Models of facilities, here we specifically deal with the reconstruction of simply-shaped wide areas (such as walls, ceilings and floors) behind furniture and facility pieces in interiors. Our approach is based on a sequential updating labeling strategy in different data representation spaces. A volumetric representation is used to permit the labeling of the 3d space for different range data and the fusion of all the scene's labels to obtain one single 2d labeling image for each of the simply-shaped wide areas of the room. Based on this labeling process, our method is able both to identify the occluded regions in the wall and, through a learning technique, to infer essential parts, such as doors, windows and closets. This method was tested under difficult clutter and occlusion conditions, yielding promising results. Scans were obtained using a state of the art laser scanner operated by a professional 3d scanning service provider.

关键词： 3d data processing Computer Vision digitizers 3d Modeling Recognition

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Scan-to-BIM for 'secondary' building components

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AdVANCEd ENGINEERING INFORMATICS 2018年 37卷 119-138页

作者： Adan, Antonio Quintana, Blanca Prieto, Samuel A. Bosche, Frederic Univ Castilla La Mancha Visual Comp & Robot Lab 3D Ciudad Real Spain Heriot Watt Univ CyberBuild Lab Inst Sustainable Bldg Design Edinburgh Midlothian Scotland

Works dealing with Scan-to-BIM have, to date, principally focused on 'structural' components such as floors, ceilings and walls (with doors and windows). But the control of new facilities and the production of their corresponding as-is BIM models requires the identification and inspection of numerous other building components and objects, e.g. MEP components, such as plugs, switches, ducts, and signs. In this paper, we present a new 6d-based (XYZ + RGB) approach that processes dense coloured 3d points provided by terrestrial laser scanners in order to recognize the aforementioned smaller objects that are commonly located on walls. This paper focuses on the recognition of objects such as sockets, switches, signs, extinguishers and others. After segmenting the point clouds corresponding to the walls of a building, a set of candidate objects are detected independently in the colour and geometric spaces, and an original consensus procedure integrates both results in order to infer recognition. Finally, the recognized object is positioned and inserted in the as-is semantically-rich 3d model, or BIM model. The assessment of the method has been carried out in simulated scenarios under virtual scanning providing high recognition rates and precise positioning results. Experimental tests in real indoors using our MoPAd (Mobile Platform for Autonomous digitization) platform have also yielded promising results.

关键词： Object recognition Scan-to-BIM Automatic BIM 3d data processing

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Passing through Open/Closed doors: A Solution for 3d Scanning Robots

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SENSORS 2019年第21期19卷 4740-4740页

作者： Prieto, Samuel A. Adan, Antonio Vazquez, Andres S. Quintana, Blanca Univ Castilla La Mancha 3D Visual Comp & Robot Lab Ciudad Real 13005 Spain

In this article, a traversing door methodology for building scanning mobile platforms is proposed. The problem of passing through open/closed doors entails several actions that can be implemented by processing 3d information provided by dense 3d laser scanners. Our robotized platform, denominated as MoPAd (Mobile Platform for Autonomous digitization), has been designed to collect dense 3d data and generate basic architectural models of the interiors of buildings. Moreover, the system identifies the doors of the room, recognises their respective states (open, closed or semi-closed) and completes the aforementioned 3d model, which is later integrated into the robot global planning system. This document is mainly focused on describing how the robot navigates towards the exit door and passes to a contiguous room. The steps of approaching, door-handle recognition/positioning and handle-robot arm interaction (in the case of a closed door) are shown in detail. This approach has been tested using our MoPAd platform on the floors of buildings composed of several rooms in the case of open doors. For closed doors, the solution has been formulated, modeled and successfully tested in the Gazebo robot simulation tool by using a 4dOF robot arm on board MoPAd. The excellent results yielded in both cases lead us to believe that our solution could be implemented/adapted to other platforms and robot arms.

关键词： robotic platform robot interaction 3d data processing

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damage detection and Finite-Element Model Updating of Structural Components through Point Cloud Analysis

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JOURNAL OF AEROSPACE ENGINEERING 2018年第5期31卷 04018068-04018068页

作者： Ghahremani, Kasra Khaloo, Ali Mohamadi, Sara Lattanzi, david Walter P Moore & Assoc 1301 McKinneySuite 1100 Houston TX 77010 USA George Mason Univ Dept Civil Environm & Infrastruct Engn Fairfax VA 22030 USA

Accurate and rapid condition assessment of in-service structural components is critical to ensure safety and serviceability. One major assessment consideration is the detection and quantification of structural section loss due to deterioration, for instance, from corrosion. Modern three-dimensional (3d) imaging techniques, which generate high-resolution 3d point clouds, are capable of detecting and measuring these deteriorations. However, despite advancements in the fields of automated point cloud analysis for as-built modeling and structural inspection, the potential use of spatial 3d data for updating numerical finite-element (FE) models of structures is still an emergent topic. This paper presents a localized methodology for the automatic and systematic detection and quantification of damages in structural components using high-fidelity 3d point cloud data, followed by a corresponding local update to an FE model. In this study, 3d point cloud data of a targeted structure were first obtained by using dense structure from motion (dSfM) algorithms. Section loss damage was then identified and located through computer vision and 3d data processing techniques. In order to preserve data integrity and resolve localized high-fidelity details, direct 3d point cloud comparisons were performed. An experimental study validating the developed approach is presented as well. The results indicate that the presented methodology will enable engineers to use the updated structural model to determine the reserved capacity and remaining service life of structural elements, though further studies on methods to improve mesh generation and defect quantification are warranted.

关键词： Three-dimensional (3d) reconstruction Condition assessment Computer vision damage detection Finite-element model Computational mechanics Structural damage digital image correlation Infrastructure monitoring 3d data processing

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Automatic building accessibility diagnosis from point clouds

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AUTOMATION IN CONSTRUCTION 2017年第Oct.期82卷 103-111页

作者： Balado, J. diaz-Vilarino, L. Arias, P. Soilan, M. Univ Vigo Dept Nat Resources & Environm Engn Appl Geotechnol Grp Campus Lagoas Marcosende Vigo 36310 Spain Delft Univ Technol GIS Technol OTB Res Inst Built Environm Julianalaan 134 NL-2628 BL Delft Netherlands

Building accessibility diagnosis is of high interest especially in case of people with reduced mobility. This paper proposes a methodology for automated detection of inaccessible steps in building fa ade entrances from MLS (mobile laser scanner) data. Our approach uses the MLS trajectory to automatically subdivide urban point clouds into regular stretches. From each stretch, the lower zone of fa ade is isolated and selected as region of interest. Points belonging to vertical elements are projected onto a 2d image and steps are detected and classified as inaccessible areas according to the comparison of geometrical features such as height jump, proximity to ground and width, with regulation. The methodology has been tested in four real datasets, which constitute > 400 m of different urban scenarios. Results exhibit a robust performance under urban scenes with a high variability of fa ade geometry due to the presence of different entrance types to shops and dwellings. Results have been quantitatively evaluated and they show global F1 value around 93%. Moreover, the methodology is very fast since 100 m are processed in < 2 min.

关键词： Building accessibility Building information modelling Indoor-outdoor seamless 3d data processing Obstacle detection Point clouds Mobile Laser Scanning 3d urban as-built

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