Search results for "Point Cloud"

showing 10 items of 81 documents

Autonomous 3D geometry reconstruction through robot-manipulated optical sensors

2021

Abstract Many industrial sectors face increasing production demands and need to reduce costs, without compromising the quality. Whereas mass production relies on well-established protocols, small production facilities with small lot sizes struggle to update their highly changeable production at reasonable costs. The use of robotics and automation has grown significantly in recent years, but extremely versatile robotic manipulators are still not commonly used in small factories. Beside of the investments required to enable efficient and profitable use of robot technology, the efforts needed to program robots are only economically viable in case of large lot sizes. Generating robot programs f…

0209 industrial biotechnologyComputer scienceReal-time computingPoint cloud02 engineering and technologyMetrologyIndustrial and Manufacturing EngineeringField (computer science)020901 industrial engineering & automationSoftware0202 electrical engineering electronic engineering information engineeringView planning3D reconstructionbusiness.industryAdaptive mappingMechanical EngineeringInspection3D reconstructionRoboticsRoboticsAutomationComputer Science ApplicationsControl and Systems EngineeringTrajectoryRobot020201 artificial intelligence & image processingArtificial intelligencebusinessSoftware
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High Quality Reconstruction of Dynamic Objects using 2D-3D Camera Fusion

2017

International audience; In this paper, we propose a complete pipeline for high quality reconstruction of dynamic objects using 2D-3D camera setup attached to a moving vehicle. Starting from the segmented motion trajectories of individual objects, we compute their precise motion parameters, register multiple sparse point clouds to increase the density, and develop a smooth and textured surface from the dense (but scattered) point cloud. The success of our method relies on the proposed optimization framework for accurate motion estimation between two sparse point clouds. Our formulation for fusing it closest-point and it consensus based motion estimations, respectively in the absence and pres…

2D-3D FusionPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyIterative reconstructionRANSAC[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Vehicle dynamics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Robustness (computer science)Motion estimationPoint Cloud Registration0502 economics and business[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionComputingMethodologies_COMPUTERGRAPHICS050210 logistics & transportationRANSACbusiness.industry05 social sciences3D reconstruction[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]020207 software engineeringICPGeography[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Artificial intelligencebusiness3D ReconstructionSurface reconstruction
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Camera-LiDAR Data Fusion for Autonomous Mooring Operation

2020

Author's accepted manuscript. © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The use of camera and LiDAR sensors to sense the environment has gained increasing popularity in robotics. Individual sensors, such as cameras and LiDARs, fail to meet the growing challenges in complex autonomous systems. One such scenario is autonomous mooring, where the ship has to …

business.industryComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONPoint cloudRobotics02 engineering and technologySensor fusionMooringGeneralLiterature_MISCELLANEOUSLidarVDP::Teknologi: 500::Maskinfag: 5700202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationComputer visionArtificial intelligencebusinessPoseCamera resectioning2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA)
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3D RECONSTRUCTION OF THE ROMAN DOMUS IN THE ARCHAEOLOGICAL SITE OF LYLIBAEUM (MARSALA, ITALY)

2019

Abstract. Generally, terrestrial laser scanning surveys involve a rather large number of scans to ensure a high percentage of overlap required for the scan registration phase (target-based or point-based registration, cloud-to-cloud registration). These approaches result in data redundancy that could slow down both the acquisition and post-processing phases. In recent years, the technological evolution in the field of laser scanners has been directed to the development of devices that are able to perform an onsite pre-registration, to optimize the survey procedures and the reliability of the registration of the scan. The paper presents the results achieved during a terrestrial laser scannin…

lcsh:Applied optics. PhotonicsTerrestrial laser scanning010504 meteorology & atmospheric sciencesLaser scanningComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION0211 other engineering and technologiesPoint cloud02 engineering and technologyScan registrationlcsh:Technology01 natural sciencesData acquisition021101 geological & geomatics engineering0105 earth and related environmental scienceslcsh:T3D reconstructionlcsh:TA1501-1820Terrestrial laser scanningTopographic mapArchaeology3D modellingPoint cloudArchaeologylcsh:TA1-2040lcsh:Engineering (General). Civil engineering (General)3D ReconstructionSettore ICAR/06 - Topografia E CartografiaThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Rilievi laser scanner con tecniche di registrazione in situ: il sistema Topcon GLS2000 per il rilievo di siti archeologici

Il lavoro svolto presenta i risultati ottenuti durante una campagna di rilievi laser scanner in ambito archeologico effettuata utilizzando il sistema GLS2000 della Topcon. Le attività di rilievo sono state condotte per la documentazione e ricostruzione tridimensionale della Domus romana all’interno del Parco archeologico di Lilibeo a Marsala. Lo scopo del lavoro è stato quello di utilizzare e verificare le tecniche di registrazione in situ impiegando, in particolare, il metodo della poligonale.

Laser scanning archeologia rilievo 3D point cloudSettore ICAR/06 - Topografia E Cartografia
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Real-Time Human Pose Estimation from Body-Scanned Point Clouds

2015

International audience; This paper presents a novel approach to estimate the human pose from a body-scanned point cloud. To do so, a predefined skeleton model is first initialized according to both the skeleton base point and its torso limb obtained by Principal Component Analysis (PCA). Then, the body parts are iteratively clustered and the skeleton limb fitting is performed, based on Expectation Maximization (EM). The human pose is given by the location of each skeletal node in the fitted skeleton model. Experimental results show the ability of the method to estimate the human pose from multiple point cloud video sequences representing the external surface of a scanned human body; being r…

Computer sciencebusiness.industryHuman pose estimationPoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]TorsoMissing data3D pose estimation[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicine.anatomical_structure[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Expectation–maximization algorithmPrincipal component analysismedicineComputer visionPoint (geometry)Artificial intelligencebusinessskeleton modelPoseComputingMethodologies_COMPUTERGRAPHICSpoint cloud
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Summarizing Large Scale 3D Point Cloud for Navigation Tasks

2017

International audience; Democratization of 3D sensor devices makes 3D maps building easier especially in long term mapping and autonomous navigation. In this paper we present a new method for summarizing a 3D map (dense cloud of 3D points). This method aims to extract a summary map facilitating the use of this map by navigation systems with limited resources (smartphones, cars, robots...). This Vision-based summarizing process is applied in a fully automatic way using the photometric, geometric and semantic information of the studied environment.

0209 industrial biotechnologyComputer scienceProcess (engineering)business.industry[INFO.INFO-RB] Computer Science [cs]/Robotics [cs.RO][ INFO.INFO-RB ] Computer Science [cs]/Robotics [cs.RO]Point cloud020206 networking & telecommunicationsCloud computing02 engineering and technologyTerm (time)020901 industrial engineering & automationHuman–computer interaction0202 electrical engineering electronic engineering information engineering[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]RobotScale (map)business
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Industrial Environment Mapping Using Distributed Static 3D Sensor Nodes

2018

This paper presents a system architecture for mapping and real-time monitoring of a relatively large industrial robotic environment of size 10 m × 15 m × 5 m. Six sensor nodes with embedded computing power and local processing of the 3D point clouds are placed close to the ceiling. The system architecture and data processing is based on the Robot Operating System (ROS) and the Point Cloud Library (PCL). The 3D sensors used are the Microsoft Kinect for Xbox One and point cloud data is collected at 20 Hz. A new manual calibration procedure is developed using reflective planes. The specified range of the used sensor is 0.8 m to 4.2 m, while depth data up to 9 m is used in this paper. Despite t…

Data processingComputer scienceReal-time computingPoint cloud0102 computer and information sciences02 engineering and technologyCeiling (cloud)01 natural sciences020202 computer hardware & architecture010201 computation theory & mathematics0202 electrical engineering electronic engineering information engineeringBenchmark (computing)Systems architectureCalibrationMetreReflection mapping2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)
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Range-based versus automated markerless image-based techniques for rock art documentation

2014

Nowadays there is a huge proliferation of fully automatic image-based solutions producing either three-dimensional (3D) point clouds or 3D models. However, the reliability of the output is not usually reported and clarified. This paper presents a comparison of the 3D modelling results achieved on two rock art shelters at separate archaeological sites using a high-resolution digital camera. The 3D point clouds were produced using automatic image-based photogrammetric and computer vision software running either locally (FOTOGIFLE and VisualSFM) or through a webbased reconstruction service (Autodesk 123D Catch). The first two automatic approaches are compared with a manual bundle block adjustm…

Terrestrial laser scanningComputer sciencemedia_common.quotation_subjectcomputer.software_genreDocumentationExcellenceEarth and Planetary Sciences (miscellaneous)Rock artComputers in Earth SciencesEngineering (miscellaneous)media_commonMultimediaData qualityTerrestrial laser scanningComputer Science ApplicationsOrtho-imagePoint cloudINGENIERIA CARTOGRAFICA GEODESIA Y FOTOGRAMETRIAChristian ministryRock artResolutionCartographycomputerImage basedRange (computer programming)Accuracy and precision
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Scalability of GPU-Processed 3D Distance Maps for Industrial Environments

2018

This paper contains a benchmark analysis of the open source library GPU-Voxels together with the Robot Operating System (ROS) in large-scale industrial robotics environment. Six sensor nodes with embedded computing generate real-time point cloud data as ROS topics. The overall data from all sensor nodes is processed by a combination of CPU and GPU on a central ROS node. Experimental results demonstrate that the system is able to handle frame rates of 10 and 20 Hz with voxel sizes of 4, 6, 8 and 12 cm without saturation of the CPU or the GPU used by the GPU-Voxels library. The results in this paper show that ROS, in combination with GPU-Voxels, can be used as a viable solution for real-time …

0209 industrial biotechnologyComputer scienceNode (networking)Point cloud02 engineering and technologycomputer.software_genreFrame rateComputational science020901 industrial engineering & automationVoxelScalability0202 electrical engineering electronic engineering information engineeringBenchmark (computing)020201 artificial intelligence & image processingCollision detectionCentral processing unitcomputerComputingMethodologies_COMPUTERGRAPHICS2018 14th IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications (MESA)
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