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The importance of quality control in the data processing of automated pavement condition surveys in municipal networks

The importance of quality control in the data processing of ...

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Transportation Association of Canada conference and Exhibition, TAC 2020

作者： Martel, Nicolas Paquet, Christine Englobe Corp. Quebec City Canada Quebec City Canada

Automated pavement condition surveys have progressed in the past few years. Mainly developed for superior road network needs, such as highway pavements, they are now very often used in the context of surveys and analysis for municipal network pavements. At this level, quality control of the data is of primary importance to obtain accurate and repeatable results that will allow trend detection and fill the needs of municipal pavement managers. Profiler surveys for road roughness measurement and 3d imaging technologies for cracking and rutting measurements need a focus adapted to municipal networks. Special cases relating to this domain will be presented (acceleration and deceleration areas of survey vehicles, interlocking paving stones on pedestrian crosswalks, railway crossings, surface defects related to snow-removal equipment, speedbumps, unpaved and work zones). In the absence of adequate quality control of the data, each of these special cases introduces inaccurate global indicators for each segment, such as IRI (ASTM E950) and PCI (ASTM d6433). This paper pinpoints the impact of these special cases in the computed values of the indices. In some cases, IRI and PCI values differing up to an order of magnitude of 100 % have been noted between datasets before quality control and after quality control. From these findings, a few approaches to supervise quality control are introduced for the data treatment phase. These approaches are complimentary to equipment specifications prescribed by municipalities RÉSUMÉ Les relevés automatisés d'état des chaussées ont beaucoup progressé dans les dernières années. Souvent développés pour des besoins de gestion du niveau routier supérieur, comme par exemple les chaussées autoroutières, ils sont maintenant très souvent utilisés dans le contexte de relevés et d'analyses de chaussées municipales. À ce niveau, le contrôle-qualité des résultats devient très important afin de produire des données précises, répétables et permettant de

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A residual U-Net network with image prior for 3d image denoising

A residual U-Net network with image prior for 3D image denoi...

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European Signal processing conference (EUSIPCO)

作者： J. F. P. J. Abascal S. Bussod N. ducros S. Si-Mohamed P. douek C. Chappard F. Peyrin INSA-Lyon CNRS UMR 5220 U1206 Univ Lyon Lyon France B3OA CNRS UMR 7052 U 1271 University Paris Diderot Paris France

ISBN: (数字)9789082797053

ISBN: (纸本)9781728150017

denoising algorithms via sparse representation are among the state-of-the art for image restoration. On previous work, we proposed SPAdE - a sparse- and prior-based method for 3d-image denoising. In this work, we extend this idea to learning approaches and propose a novel residual-U-Net prior-based (ResPrU-Net) method that exploits a prior image. The proposed ResPrU-Net architecture has two inputs, the noisy image and the prior image, and a residual connection that connects the prior image to the output of the network. We compare ResPrU-Net to U-Net and SPAdE on human knee data acquired on a spectral computerized tomography scanner. The prior image is built from the noisy image by combining information from neighbor slices and it is the same for both SPAdE and ResPrU-Net. For deep learning approaches, we use four knee samples and data augmentation for training, one knee for validation and two for test. Results show that for high noise, U-Net leads to worst results, with images that are excessively blurred. Prior-based methods, SPAdE and ResPrU-Net, outperformed U-Net, leading to restored images that present similar image quality than the target. ResPrU-Net provides slightly better results than SPAdE. For low noise, methods present similar results.

关键词： Training Three-dimensional displays Noise reduction Signal processing algorithms Signal processing Image restoration Noise measurement

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3d-Reconstruction and Semantic Segmentation of Cystoscopic Images 1

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International conference on Medical Imaging and Computer-Aided diagnosis, MICAd 2020

作者： Negassi, M. Parupalli, U. Suarez-Ibarrola, R. Schmitt, A. Hein, S. Miernik, A. Reiterer, A. Department of Sustainable Systems Engineering INATECH University of Freiburg Freiburg Germany Fraunhofer Institute for Physical Measurement Techniques IPM Emmy-Noether-Strasse 2 Freiburg79108 Germany Department of Urology Faculty of Medicine University of Freiburg – Medical Centre Hugstetter Str 55 Freiburg79106 Germany

ISBN: (数字)9789811551994

ISBN: (纸本)9789811551987

Bladder cancer (BCa) is the fourth most common cancer and the eighth most common cause of cancer-related mortality in men. Although roughly 75% of patients are diagnosed with non-muscle invasive bladder cancer (NMIBC), recurrence rates are high even at a low stage and grade. Transurethral resection (TURB) is required for establishing the pathological diagnosis and clinical staging of patients. In daily clinical practice, however, conventional tumor documentation after TURB lacks accuracy, posing a major limitation for patient follow-up and surveillance. Novel technologies to facilitate data documentation and interpretation processes are imperative to maximize patients’ outcomes. As part of the RaVeNNA-4pi initiative, our contribution is twofold: first, we propose a bladder 3d-reconstruction method using Structure-from-Motion (SfM). Second, we propose deep convolutional neural networks (dCNN) for cystoscopic image segmentation to improve the interpretation of cystoscopic findings and localization of tumors. 3d reconstruction of endoscopic images assists physicians in navigating the bladder and monitoring successive resections. Nevertheless, this process is challenging due to an endoscope’s narrow field of view (FoV), illumination conditions and the bladder’s highly dynamic structure. So far in our project, the SfM approach has been tested on a bladder phantom, demonstrating that the processing sequence permits a 3d reconstruction. Subsequently, we will test our approach on bladder images from patients generated in real-time with a rigid cystoscope. In recent years, deep learning (dL) has enabled significant progress in medical image analysis. Accurate localization of structures such as tumors is of particular interest in processing medical images. In this work, we apply a dCNN for multi-class semantic segmentation of cystoscopic images. Moreover, we introduce a new training dataset for evaluating state-of-the-art dL models on cystoscopic images. Our results show that

关键词： Semantic Segmentation

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Use of imaging techniques as a support for the preventive conservation strategy of wall paintings: Application to the medieval decors of the château de germolles 9th

Use of imaging techniques as a support for the preventive co...

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9th International conference on Image and Signal processing, ICISP 2020

作者： degrigny, Christian Boochs, Frank Raddatz, Laura Veller, Jonas Justus, Carina Pinette, Matthieu Haute Ecole Arc Conservation-restauration HES-SO University of Applied Sciences and Arts Western Switzerland Espace de l’Europe 11 Neuchâtel2000 Switzerland Institute for Spatial Information and Surveying Technology University of Applied Sciences - i3Mainz Lucy-Hillebrand-Straße 2 Mainz55128 Germany Château de Germolles 100 place du 5 Septembre 1944 Mellecey71640 France

ISBN: (纸本)9783030519346

Imaging techniques were used to document and monitor physical damage to the unique wall paintings at the Château de Germolles, Burgundy, France. Photogrammetry combined with scanning are the most appropriate techniques to monitor the evolution of microcrack networks in the cornice overhanging the paintings and preserved as a witness to 19th century additions. However, the application of these techniques was challenged due to the given constraints of a working height of 4 m and the required accuracy of a tenth of a millimetre. A special effort was therefore necessary to ensure sufficient stability of the acquisition protocol and to make it relevant during the four measurement campaigns planned over the two years of the project. The analysis of photogrammetric data has made it possible to document certain macro-deformations of the cornice according to the seasons of the year. The microcracks could be visualized and monitored from transformed 3d models of each segment for the different campaigns. The results obtained show only local movements, mainly on the walls that are most exposed to the specific climatic conditions of each season. © Springer Nature Switzerland AG 2020.

关键词： Photogrammetry

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denoising method of rail point cloud data based on morphological filtering

Denoising method of rail point cloud data based on morpholog...

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International conference on Signal processing Proceedings (ICSP)

作者： Qiang Han Hongwei Zhao Le Wang Shengchun Wang Qibo Feng School of Science Beijing Jiaotong University School of Computer and Information Technology Beijing Jiaotong University China Academy of Railway Sciences Corporation Limited Beijing China

ISBN: (数字)9781728144801

ISBN: (纸本)9781728144818

When using a three-dimensional point cloud scanner to collect data points, due to the influence of various uncertain factors, the data points obtained by the three-dimensional electronic scanning device are always mixed with some noise points. If the noise contained in the point cloud is not filtered through technical methods, these noises will definitely have an impact on the subsequent extraction and recognition of the target set characteristics. Therefore, based on the accurate acquisition of 3d data, we research and design a fast denoising preprocessing algorithm that can be used for high-density 3d data to provide more accurate and effective 3d measurement data for subsequent 3d reconstruction and recognition processing.

关键词： Three-dimensional displays Filtering Wiener filters Kernel Nonlinear filters Maximum likelihood detection Morphology

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5th Asian conference on Pattern Recognition,ACPR 2019

5th Asian Conference on Pattern Recognition,ACPR 2019

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5th Asian conference on Pattern Recognition,ACPR 2019

ISBN: (纸本)9789811536502

The proceedings contain 23 papers. The special focus in this conference is on Pattern Recognition. The topics include: vi-MoCoGAN: A Variant of MoCoGAN for Video Generation of Human Hand Gestures Under different Viewpoints;weakly Supervised domain Adaptation with Point Supervision in Histopathological Image Segmentation;blood Vessel Enhancement in Liver Region from a Sequence of Angiograms Taken under Free Breathing;real-Time Morphing of the Visible Man Liver with Intrahepatic Vasculatures;development of 3d Physiological Simulation and Education Software for Pregnant Women;resolution Conversion of Volumetric Array data for Multimodal Medical Image Analysis;learning Spatiotemporal Representation Based on 3d Autoencoder for Anomaly detection;multi-view discriminant Analysis for dynamic Hand Gesture Recognition;human Action Recognition Based on dual Correlation Network;Bypass Enhancement RGB Stream Model for Pedestrian Action Recognition of Autonomous Vehicles;feature Engineering Workflow for Activity Recognition from Synchronized Inertial measurement Units;Infrared-Image processing for the dLR FireBIRd Mission;temperature dependence of dark Signal for Sentinel-4 detector;an Extended Stochastic Cloning Method for Fusing Multi-relative measurements;paved and Unpaved Road Segmentation Using deep Neural Network;image Scene Conversion Algorithm Based on Generative Adversarial Networks;An Embedded Real-Time Monocular SLAM System Utilizing a dynamically Reconfigurable Processor;writer Identification Based on Combination of Bag of Words Model and Multiple Classifiers;vehicle-Related Scene Understanding Using deep Learning;spatiotemporal Saliency Based Multi-stream Networks for Action Recognition;attention Guided Unsupervised Image-to-Image Translation with Progressively Growing Strategy.

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Wearable Magnetic Field based 3d-Orientation and -Position Acquisition

Wearable Magnetic Field based 3D-Orientation and -Position A...

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GLOBECOM 2020 - 2020 IEEE Global Communications conference

作者： Puian Tadayon Gerhard Staude Thomas Felderhoff Andreas Knopp Research Center for BioMedical Technology University of Applied Sciences and Arts Dortmund Germany Chair of Signal Processing (EIT 3.2) Bundeswehr University München Neubiberg Germany

ISBN: (数字)9781728182988

ISBN: (纸本)9781728182995

This paper introduces a new magnetic field based system design for 3d-orientation and -position acquisition in mobile applications for human motion analysis. The system basically consists of a source unit and a sensor unit and does not require any line of sight between its components. The source unit contains a single one-axis coil for magnetic field generation as well as a MARG sensor for 3d-orientation estimation. The sensor unit contains a single MARG sensor both for 3d-orientation and 3d-position estimation. For 3d-position estimation, a new algorithm is proposed which exploits not only the magnitude of the coil generated magnetic field, but also the phase information and thus is able to determine a unique position solution based on the data of a single 3d-magnetometer only. A wearable prototype of both the source and the sensor unit is realized and used for system verification by comparing the position data of the prototype to the data of a camera-based reference system (Vicon Vero). The verification results indicate high accuracy and repeatability of the proposed system.

关键词： Magnetic fields Magnetic field measurement Estimation Magnetometers Earth Position measurement Band-pass filters

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Comparison of deep learning and hand crafted features for mining simulation data

Comparison of deep learning and hand crafted features for mi...

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International conference on Pattern Recognition

作者： Theodoros Georgiou Sebastian Schmitt Thomas Bäck Nan Pu Wei Chen Michael Lew Leiden University Leiden Institute of Advanced Computer Science Leiden the Netherlands Honda Resarch Institute Europe GmbH Offenbach Germany

ISBN: (纸本)9781728188089;9781728188096

Computational Fluid dynamics (CFd) simulations are a very important tool for many industrial applications, such as aerodynamic optimization of engineering designs like cars shapes, airplanes parts etc. The output of such simulations, in particular the calculated flow fields, are usually very complex and hard to interpret for realistic three-dimensional real-world applications, especially if time-dependent simulations are investigated. Automated data analysis methods are warranted but a non-trivial obstacle is given by the very large dimensionality of the data. A flow field typically consists of six measurement values for each point of the computational grid in 3d space and time (velocity vector values, turbulent kinetic energy, pressure and viscosity). In this paper we address the task of extracting meaningful results in an automated manner from such high dimensional data sets. We propose deep learning methods which are capable of processing such data and which can be trained to solve relevant tasks on simulation data, i.e. predicting drag and lift forces applied on an airfoil. We also propose an adaptation of the classical hand crafted features known from computer vision to address the same problem and compare a large variety of descriptors and detectors. Finally, we compile a large dataset of 2d simulations of the flow field around airfoils which contains 16000 flow fields with which we tested and compared approaches. Our results show that the deep learning-based methods, as well as hand crafted feature based approaches, are well-capable to accurately describe the content of the CFd simulation output on the proposed dataset.

关键词： deep learning Solid modeling dictionaries Three-dimensional displays Computational modeling Atmospheric modeling detectors

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Monitoring surface degradation process by 3d structured light scanning 7

Monitoring surface degradation process by 3D structured ligh...

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conference on Optics for Arts, Architecture, and Archaeology VII

作者： Sitnik, R. Lech, K. Bunsch, E. Michonski, J. Warsaw Univ Technol Pl Politehniki 1 PL-00661 Warsaw Poland Museum King Jan IIIs Palace Wilanow Ul Stanislawa Kostki Potockiego 10-16 PL-02958 Warsaw Poland

ISBN: (数字)9781510627963

ISBN: (纸本)9781510627963

In our paper we will present results of an on-going project connected with monitoring the condition of 12 fragments of the Museum of King Jan III's Palace at Wilanow (Warsaw, Poland) building faCade by 3d structured-light scanning method. during 30 months, 7 series of three-dimensional measurements have been planned. In each of the twelve elevation fragments, chosen by the conservation and architecture departments as particularly interesting, an area of 120 mm x 120 mm was scanned with 2500 points/mm(2) resolution. This article describes the methodology of the measurement process, the hardware setup developed especially for this purpose, as well as the data processing path and analysis algorithms. In addition to having such accurate measurement data, we must still be able to match the measurements carried out in the same place at intervals of several months For this purpose the areas of interest were marked with special aluminum targets, embedded with three intersecting planes. The algorithm of their detection, analysis and use for aligning data from subsequent measurement series is discussed. A portable SLS 3d-measurement head with two cameras, integrated with linear drive has been developed for scanning purposes and adopted to use in outdoor condition. The 3d scanner has a measurement volume limited to 45 mm x 50 mm x 10 mm for a single scan, due to high-resolution requirements. In less than 25 minutes, 40 measurements are acquired at various positions, covering the entire area, with the support of a controlled linear stage stand. Individual scans are pre-aligned with limited accuracy and then fitted using the Iterative Closest Point algorithm. The final representation of each fragment is a cloud of points with color containing more than 200 million 3d measurement points. We present the results of 3d measurements and a proposition of a monitoring procedure for assessing the change in 3d surfaces over time.

关键词： 3d scanning structured light preventive conservation surface degradation monitoring

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Low-cost 3d scanning using ultrasonic and camera data fusion for CNC Engraving Laser-Based Machine

Low-cost 3D scanning using ultrasonic and camera data fusion...

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Iranian Machine Vision and Image processing (MVIP)

作者： Meisam Jamshidi Seikavandi Nikoo Dana fanavari Delfan Technology and Science Park of Lorestan Iran

ISBN: (数字)9781728168326

ISBN: (纸本)9781728168333

Sensor-fusion has gained much popularity in 3dscanning in recent years. There are a variety of sensors like depth-camera, camera, laser-scanner, ultrasonic sensor, which are widely used in the area. The robotic research community has studied ultrasound sensors for decades. While they have lost attention with the advent of laser scanners and cameras, they remain successful for special applications due to their robustness and simplicity; additionally, ultrasound measurement is more robust than depth-camera for illumination-varying scenarios and work with glassy pieces. In this work, we choose camera and ultrasonic sensor fusion method for a CNC Engraving Machine concerning their lower cost and a particular act of applying. We use a heuristic, hand-crafted fusion to prepare 3d presentation of different pieces. The output data of the camera were down-sampled to ultrasonic data scale. By using an image processing method, the image, and ultrasonic data will be used to prepare a principle scheme and final 3d map.

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