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Utility pole extraction processing from point cloud data from 3d measurement and its applications

Utility pole extraction processing from point cloud data fro...

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International conference on Awareness Science and Technology (iCAST)

作者： Zhiyi Gao Akio doi Toru Kato Hiroki Takahashi Kenji Sakakibara Tomonori Hosokawa Masahiro Harada Graduate School of Software and Information Science Iwate Prefectural University 152–52 Sugo Takizawa-shi Iwate-ken Japan TOKU/PCM Co. Ltd. Morioka-shi Iwate-ken Japan Tuck Engineering Co. Ltd. Morioka-shi Iwate-ken Japan

ISBN: (数字)9781728191195

ISBN: (纸本)9781728191201

In this study, we propose a method to automatically remove utility poles and electric parts from 3d measurement data of shopping streets and roads, and be used for the landscape simulation of underground utility poles construction at Suehiro-cho of Miyako City. In this method, utility poles were stably extracted automatically by using plural rectangular volumes, Hough transform, and two-dimensional Gaussian function. The efficiency of processing is improved by five times compared with the interactive method of removing the utility poles and the electric parts by the dialogue processing.

关键词： Three-dimensional displays Two dimensional displays Transforms data mining Feature extraction Software Roads

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2nd International conference on Human Systems Engineering and design: Future Trends and Applications, IHSEd 2019

2nd International Conference on Human Systems Engineering an...

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2nd International conference on Human Systems Engineering and design: Future Trends and Applications, IHSEd 2019

ISBN: (纸本)9783030279271

The proceedings contain 162 papers. The special focus in this conference is on Human Systems Engineering and design: Future Trends and Applications. The topics include: Lean and Ergonomics Competencies: Knowledge and Applications;preprocessing Information from a data Network for the detection of User Behavior Patterns;designing an e-Coach to Tailor Training Plans for Road Cyclists;half Scale dress Forms from 3d Body Scans in Active Poses;a Comparison of Heart Rate in Normal Physical Activity vs. Immersive Virtual Reality Exergames;the Impact of Ergonomic design on Smart Garments;user Centered design of a Pill dispenser for the Elderly;The Importance of ICT and Wearable devices in Monitoring the Health Status of Coronary Patients;improvement of a Monitoring System for Preventing Elderly Fall down from a Bed;ergonomic design Process of the Shape of a diagnostic Ultrasound Probe;autonomous Learning Mediated by digital Technology Processes in Higher Education: A Systematic Review;discussion on the Effect of Bedding on Sleep Postures;design Culture Within the B2B Needs Roadmap;masticatory Evaluation in Non-contact measurement of Chewing Movement;satisfaction of Aged Users with Mobility Assistive devices: A Preliminary Study of Conventional Walkers;effect of Added Mass Location on Manual Wheelchair Propulsion Forces;Exploration of TCM Health Service Mode in the Context of Aging Society;standardized Research of Clinical diagnosis and Treatment data of Epilepsy;experience design: A Tool to Improve a Child’s Experience in the Use of Vesical Catheters;human Aspects in Product and Service development;potential of Industrial Image processing in Manual Assembly.

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Optical Non-Line-of-Sight Physics-Based 3d Human Pose Estimation

Optical Non-Line-of-Sight Physics-Based 3D Human Pose Estima...

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conference on Computer Vision and Pattern Recognition (CVPR)

作者： Mariko Isogawa Ye Yuan Matthew O'Toole Kris Kitani Carnegie Mellon University

ISBN: (数字)9781728171685

ISBN: (纸本)9781728171692

We describe a method for 3d human pose estimation from transient images (i.e., a 3d spatio-temporal histogram of photons) acquired by an optical non-line-of-sight (NLOS) imaging system. Our method can perceive 3d human pose by 'looking around corners' through the use of light indirectly reflected by the environment. We bring together a diverse set of technologies from NLOS imaging, human pose estimation and deep reinforcement learning to construct an end-to-end data processing pipeline that converts a raw stream of photon measurements into a full 3d human pose sequence estimate. Our contributions are the design of data representation process which includes (1) a learnable inverse point spread function (PSF) to convert raw transient images into a deep feature vector; (2) a neural humanoid control policy conditioned on the transient image feature and learned from interactions with a physics simulator; and (3) a data synthesis and augmentation strategy based on depth data that can be transferred to a real-world NLOS imaging system. Our preliminary experiments suggest that our method is able to generalize to real-world NLOS measurement to estimate physically-valid 3d human poses.

关键词： Transient analysis Three-dimensional displays Nonlinear optics Imaging Pose estimation Humanoid robots Feature extraction

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Learning-Based Shape Estimation with Grid Map Patches for Realtime 3d Object detection for Automated driving

Learning-Based Shape Estimation with Grid Map Patches for Re...

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International conference on Intelligent Transportation

作者： Hendrik Königshof Christoph Stiller Intelligent Systems and Production Engineering FZI Research Center for Information Technology Karlsruhe Germany Institute of Measurement and Control Systems Karlsruhe Institute of Technology (KIT) Karlsruhe Germany

ISBN: (数字)9781728141497

ISBN: (纸本)9781728141503

3d object detection serves as a crucial basis of visual perception, motion prediction, and planning for automated driving. To apply an algorithm for this purpose, the detection of all types of road users in real-time is an essential condition. In this paper, we propose an approach that projects the 3d points of image-based bounding box proposals into so-called grid map patches. These patches are used to estimate the exact dimensions of the 3d box with the help of a lightweight CNN. The complete proposed processing chain is parallelized and implemented on a GPU. This makes our approach the fastest stereo-based 3d object detector on the KITTI benchmark while still achieving results that are within the range of the best image-based algorithms.

关键词： Three-dimensional displays Encoding Two dimensional displays Shape Object detection Estimation Training data

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An Acceleration Algorithm of 3d Point Cloud Registration Based on Iterative Closet Point

An Acceleration Algorithm of 3D Point Cloud Registration Bas...

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Image processing, Electronics and Computers (IPEC), Asia-Pacific conference on

作者： Tianyu Ren Ruicheng Wu School of Computer Science and Technology Harbin Institute of Technology Weihai China

ISBN: (数字)9781728160672

ISBN: (纸本)9781728160689

We propose a novel method for 3d point cloud registration. By considering first order approximation to the data point, our algorithm finds more accurate point pairs than using the closet point strategy. Moreover, we use a new distance error measurement in the ICP framework which considers the second order geometry information rather the first order geometry information in the popular point-plane distance error. Experimental results show that the proposed scheme not only speeds up the convergence of registration, but also eliminates wrong pairing of data points. Both the efficiency of point cloud data registration and the performance of the algorithm have been significantly improved compared with the state-of-the-art methods.

关键词： point cloud registration iterative closet point distance field distance error function optimization Iterative closest point algorithm Registration Point pairs Information geometry algorithms Clouds

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40th Anniversary International conference on Information Systems Architecture and Technology, ISAT 2019

40th Anniversary International Conference on Information Sys...

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40th Anniversary International conference on Information Systems Architecture and Technology, ISAT 2019

ISBN: (纸本)9783030304393

The proceedings contain 87 papers. The special focus in this conference is on Information Systems Architecture and Technology. The topics include: A Generic Approach to Schema Evolution in Live Relational databases;the Concept of a Flexible database - Implementation of Inheritance and Polymorphism;UAV detection Employing Sensor data Fusion and Artificial Intelligence;heuristic Algorithm for Recovering a Physical Structure of Spreadsheet Header;a Web-Based Support for the Management and Evaluation of measurement data from Stress-Strain and Continuous-Cooling-Transformation Experiments;software Toolkit for Visualization and Process Selection for Modular Scalable Manufacturing of 3d Micro-devices;verification of IoT devices by Means of a Shared Secret;A Secure IoT Firmware Update Framework Based on MQTT Protocol;detection of Intrusions to Web System Using Computational Intelligence;Context-Aware Indexing and Retrieval for Cognitive Systems Using SOEKS and ddNA;new Encryption Method with Adaptable Computational and Memory Complexity Using Selected Hash Function;OSAA: On-demand Source Authentication and Authorization in the Internet;analysis of Blockchain Selfish Mining Attacks;cooperation of Neuro-Fuzzy and Standard Cloud Web Brokers;microservice-Based Cloud Application Ported to Unikernels: Performance Comparison of different Technologies;a Study on Effectiveness of processing in Computational Clouds Considering Its Cost;webAssembly – Hope for Fast Acceleration of Web Applications Using JavaScript;measured vs. Perceived Web Performance;Resource Management for Sd-WANs;Quality of data Transmission in the Access Points of PWR-WiFi Wireless Network;designing Information Integrating Systems Based on Co-shared Ontologies;information Systems Architecture and Technology Security Aspects Relating to the Usability Attributes and Evaluation Methods of Mobile Commerce Websites.

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Graphite: Graph-Induced Feature Extraction for Point Cloud Registration

Graphite: Graph-Induced Feature Extraction for Point Cloud R...

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International conference on 3d Imaging, Modeling, processing, Visualization and Transmission (3dIMPVT)

作者： Mahdi Saleh Shervin dehghani Benjamin Busam Nassir Navab Federico Tombari Technische Universität München Google

ISBN: (数字)9781728181288

ISBN: (纸本)9781728181295

3d Point clouds are a rich source of information that enjoy growing popularity in the vision community. However, due to the sparsity of their representation, learning models based on large point clouds is still a challenge. In this work, we introduce Graphite, a GRAPH-Induced feaTure Extraction pipeline, a simple yet powerful feature transform and keypoint detector. Graphite enables intensive down-sampling of point clouds with keypoint detection accompanied by a descriptor. We construct a generic graph-based learning scheme to describe point cloud regions and extract salient points. To this end, we take advantage of 6d pose information and metric learning to learn robust descriptions and keypoints across different scans. We Reformulate the 3d keypoint pipeline with graph neural networks which allow efficient processing of the point set while boosting its descriptive power which ultimately results in more accurate 3d registrations. We demonstrate our lightweight descriptor on common 3d descriptor matching and point cloud registration benchmarks [76], [71] and achieve comparable results with the state of the art. describing 100 patches of a point cloud and detecting their keypoints takes only 0.018 seconds with our proposed network.

关键词： Three-dimensional displays Feature extraction Graphite Pipelines measurement data mining Two dimensional displays

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Analytical Change detection on the KITTI dataset

Analytical Change Detection on the KITTI dataset

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International conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Johannes Schauer Marin Rodrigues Andreas Nüchter Julius-Maximilians-University Wurzburg Germany Robotics and Telematics Julius-Maximilians-University Würzburg Germany

ISBN: (数字)9781728177090

ISBN: (纸本)9781728177106

We present an algorithm for explicit change detection on 3d point cloud data from a mobile mapping scenario, namely the KITTI dataset. Our method is able to partition a 3d point cloud into static and dynamic points using ray traversal of a 3d voxel grid. We are thus not using a machine learning approach or RGB camera data but instead compute the intersections of the scene volume with the lines-of-sight between the sensor and the measured points. Our approach does thus not require any object detection or tracking and has comparatively low requirements on the hardware. While our earlier work focused on dense point clouds from terrestrial 3d laser scans, here we investigate its application on the sparse 3d point clouds produced by a Velodyne laser range finder in a mobile mapping scenario and compare our results to two competing implementations using the ground truth annotation from FuseMOdNet for a quantitative analysis. We also introduce spherical quadtree point cloud reduction as a way to only work on less than 1% of the original data, making processing multiple times faster while at the same time producing results with equivalent F 1 scores.

关键词： Three-dimensional displays Cameras Benchmark testing Volume measurement Heuristic algorithms Geometry data structures

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Spatially Constrained Likeliness-based Fuzzy Entropy Clustering Algorithm and its Application to Noisy 3d Brain MR Image Segmentation

Spatially Constrained Likeliness-based Fuzzy Entropy Cluster...

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IEEE Applied Signal processing conference (ASPCON)

作者： Nabanita Mahata Jamuna Kanta Sing Jadavpur University Kolkata India

ISBN: (数字)9781728168821

ISBN: (纸本)9781728168838

This paper proposes a spatially constrained likeliness-based fuzzy entropy clustering algorithm for noisy 3d brain MR image segmentation. It introduces a likeliness measure with respect to a voxel under consideration by using intensity distribution surrounding its local neighborhood. We use this measure as an additional membership function and named as fuzzy likeliness measures. We integrate these two fuzzy membership functions into a objective function by means of a regularizing parameter. Further, we introduce a fuzzy entropy using the fuzzifier weighted fuzzy likeliness measures to define the information uncertainty associated with a voxel in order to finding its cluster. By integrating weighted fuzzy membership function and fuzzy likeliness measure we generate the final membership function. The experiments on noisy 3d brain MR image volumes that include simulated and clinical data suggest that the proposed algorithm is superior while comparing with several state-of-the-art algorithms in terms of dice coefficient, partition coefficient and partition entropy.

关键词： Signal processing algorithms Entropy Clustering algorithms Three-dimensional displays Partitioning algorithms Image segmentation Weight measurement

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Improving Psnr-Based Quality Metrics Performance For Point Cloud Geometry

Improving Psnr-Based Quality Metrics Performance For Point C...

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IEEE International conference on Image processing

作者： Alireza Javaheri Catarina Brites Fernando Pereira João Ascenso Instituto Superior Técnico – Universidade de Lisboa and Instituto de Telecomunicações

ISBN: (数字)9781728163956

ISBN: (纸本)9781728163963

An increased interest in immersive applications has drawn attention to emerging 3d imaging representation formats, notably light fields and point clouds (PCs). Nowadays, PCs are one of the most popular 3d media formats, due to recent developments in PC acquisition, namely with new depth sensors and signal processing algorithms. To obtain high fidelity 3d representations of visual scenes a huge amount of PC data is typically acquired, which demands efficient compression solutions. As in 2d media formats, the final perceived PC quality plays an importance role in the overall user experience and, thus, objective metrics capable to measure the PC quality in a reliable way are essential. In this context, this paper proposes and evaluates a set of objective quality metrics for the geometry component of PC data, which plays a very important role on the final perceived quality. Based on the popular PSNR PC geometry quality metric, novel improved PSNR-based metrics are proposed by exploiting the intrinsic PC characteristics and the rendering process that must occur before visualization. The experimental results show the superiority of the best proposed metrics over state-of-the-art, obtaining an improvement up to 32% in the Pearson correlation coefficient.

关键词： measurement Geometry Visualization Three-dimensional displays Media Rendering (computer graphics) User experience

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