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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VI"

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A microservice-based building block approach for scientific workflow engines: processing large data volumes with dagonstar 15

A microservice-based building block approach for scientific ...

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15th International conference on Signal image Technology and Internet Based systems, SISITS 2019

作者： Sanchez-Gallegos, Dante D. Di Luccio, Diana Gonzalez-Compean, J.L. Montella, Raffaele Unidad Tamaulipas Cinvestav Victoria Mexico Dpt. of Science and Technologies University of Naples Parthenope Naples Italy

ISBN: (纸本)9781728156866

The impact of machine learning algorithms on everyday life is overwhelming until the novel concept of datacracy as a new social paradigm. In the field of computational environmental science and, in particular, of applications of large data science proof of concept on the natural resources management this kind of approaches could make the difference between species surviving to potential extinction and compromised ecological niches. In this scenario, the use of high throughput workflow engines, enabling the management of complex data flows in production is rock solid, as demonstrated by the rise of recent tools as Parsl and DagOnStar. Nevertheless, the availability of dedicated computational resources, although mitigated by the use of cloud computing technologies, could be a remarkable limitation. In this paper, we present a novel and improved version of DagOnStar, enabling the execution of lightweight but recurring computational tasks on the microservice architecture. We present our preliminary results motivating our choices supported by some evaluations and a real-world use case. © 2019 IEEE.

关键词： Cloud computing

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An ISAR Approach for Refocusing the Maritime Moving Targets with the GF-3 SAR Satellite 6

An ISAR Approach for Refocusing the Maritime Moving Targets ...

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6th Asia-Pacific conference on Synthetic Aperture Radar, APSAR 2019

作者： Yan, Zhishuo Zhang, Yi Wang, Robert Zhang, Heng Yu, Weidong Institute of Electronics Chinese Academy of Sciences Department of Space Microwave Remote Sensing Systems Beijing China School of Electronics Electrical and Communication Engineering University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781728129129

Moving ship targets are always defocused in synthetic aperture radar (SAR) images under the influence of self-motion and sea waves. Inverse SAR (ISAR) technique is commonly used to focus non-cooperative targets by motion compensation. A novel refocusing method, improved rank one phase estimation (IROPE), is proposed in this paper. The ISAR processing is based on the proposed method, an iterative two-step convergence approach to obtain the phase error. The performance of the proposed method is tested by comparing it to other focusing algorithms using real spotlight complex image data of Gaofen-3 (GF-3) spaceborne SAR system. Results verify the effectiveness of the proposed method. © 2019 IEEE.

关键词： Motion compensation

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Intelligent Detection of Object's Anomalies for Road Surveilance Cameras

Intelligent Detection of Object's Anomalies for Road Surveil...

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2019 International Multi-conference on Engineering, Computer and Information Sciences, SIBIRCON 2019

作者： Makhmutova, Alisa Minnikhanov, Rifkat Dagaeva, Maria Anikin, Igor Bolshakov, Tikhon Khuziakhmetov, Ilnur ITS Center Road Safety State Company Kazan Russia Main Office Road Safety State Company Kazan Russia Kazan National Research Technical University Named after A.N. Tupolev-KAI Information Security Systems Department Kazan Russia

ISBN: (纸本)9781728144016

Nowadays intelligent data processing tools are widely applying into cities infrastructure in order to make citizent's life safer and convenient. One of the most important part of it is video surveillance, which plays important role in many traffic flow monitoring applications. Recent advances in hardware, computer vision and machine learning techniques makes it possible to solve different tasks for applications in real time without human, including recognition of different objects, anomalies and incidents detection. In this paper, we analyzed the impact of image pre-processing technique such as grayscaling on our AI based object detection and tracking model. We also used machine learning algorithms to detect object's frequent trajectories and anomalies on real time video from road surveillance cameras. Based on this, we suggested an approach to detect violations of legal trajectories by vehicles or pedes trians. © 2019 IEEE.

关键词： Computer vision

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UAV detection, tracking and classification by sensor fusion of a 360° LiDAR system and an alignable classification sensor 24

UAV detection, tracking and classification by sensor fusion ...

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conference on Laser Radar Technology and Applications XXIV

作者： Hammer, Marcus Borgmann, Bjoern Hebel, Marcus Arens, Michael Fraunhofer Inst Optron Syst Technol & Image Explo Gutleuthausstr 1 D-76275 Ettlingen Germany

ISBN: (纸本)9781510626768

The number of reported incidents caused by UAVs, intentional as well as accidental, is rising. To avoid such incidents in future, it is essential to be able to detect UAVs. However, not every UAV is a potential threat and therefore the UAV not only has to be detected, but classified or identified. 360 degrees scanning LiDAR systems can be deployed for the detection and tracking of (micro) UAVs in ranges up to 50 m. Unfortunately, the verification and classification of the detected objects is not possible in most cases, due to the low resolution of that kind of sensor. In this paper, we propose an automatic alignment of an additional sensor (mounted on a pan-tilt head) for the identification of the detected objects. The classification sensor is directed by the tracking results of the panoramic LiDAR sensor. If the alignable sensor is an RGB- or infrared camera, the identification of the objects can be done by state-of-the-art image processing algorithms. If a higher-resolution LiDAR sensor is used for this task, algorithms have to be developed and implemented. For example, the classification could be realized by a 3D model matching method. After the handoff of the object position from the 360 degrees LiDAR to the verification sensor, this second system can be used for a further tracking of the object, e.g., if the trajectory of the UAV leaves the field of view of the primary LiDAR system. The paper shows first results of this multi-sensor classification approach.

关键词： 3D object detection 360 degrees LiDAR scans UAV detection UAV tracking scanline analysis

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Evaluation of the geometric and radiometric accuracy across the European Space Agency (ESA) Landsat historical archive 25

Evaluation of the geometric and radiometric accuracy across ...

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conference on image and Signal processing for Remote Sensing XXV

作者： Saunier, Sebastien Melchiorre, Andrea Lavender, Samantha Beaton, Amy Mica, Stefano Di Erasmo, Daniele Biasutti, Roberto Ottavianelli, Giuseppe Boccia, Valentina Telespazio VEGA UK Ltd IDEAS Luton Beds England Exprivia IDEAS Via Bufalotta 378 I-00139 Rome Italy Serco IDEAS Via Sciadonna 24 I-00044 Frascati Italy ESA ESRIN Earth Observat Programme Via Galileo Galilei Frascati Italy

ISBN: (数字)9781510630147

ISBN: (纸本)9781510630147

In the context of Long Term Data Preservation, ESA, with the support of the Instrument Data Evaluation and Quality Analysis Service (IDEAS+) team, reprocessed over 600'000 Landsat 1-5 Multi-Spectral Scanner (MSS) products acquired in the period 1975 - 2001 from the European Ground Stations complementing the existing 1 million Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) Level 1 products, with a geographical coverage from Greenland to Continental Europe and North Africa. The reprocessing software and quality control tool developed for the reprocessing present new features aimed at improving the radiometric and geometric accuracy, image data recovery and including additional quality assurance information. An accurate geometric and radiometric accuracy evaluation across the over 40-years long operative life of Landsat is vital for the exploitation of long time series analysis and for the future development of multi-mission Analysis Ready Data (ARD). This paper proposes to evaluate the geometric accuracy and the radiometric calibration accuracy of the Landsat Level 1 products delivered by ESA. It is obvious that across Landsat historical mission the accuracy is not the same;data are acquired with the MSS, the TM and the ETM+ sensors with improved characteristics for the most recent ones. All these differences between remote sensing systems, did not preclude to engineer processing algorithms with one main objective to harmonize physical measurement and ensure interoperability with the ongoing missions such as Landsat 8 - OLI / Sentinel 2 - MSI. This approach is a key aspect for the future development of multi mission ARD. The geometric quality assurance parameters are exposed in the Level 1 products. These scene based parameters allows to filter out and select, for a given region, if needed the most accurate products. Also, to demonstrate that these parameters are consistent is fundamental. Because of the ageing of missions, specifically for MSS missions

关键词： Landsat Calibration / Validation Geometry Quality Control MSS ARD Data preservation Bulk processing

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Complex field-based fusion network for human activities classification with radar

Complex field-based fusion network for human activities clas...

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IET International Radar conference (IET IRC 2020)

作者： J. Guo C. Shu Y. Zhou K. Wang F. Fioranelli O. Romain J. Le Kernec University of Glasgow Glasgow UK MS3-Microwave Sensing Signals and Systems Delft Netherlands University Cergy-Pontoise Cergy France

In the context of assisted living, human activity recognition (HAR) is of increased importance to maintain people at home living independently longer. Compared with directly using spectrograms (μD) or range profiles (RP) as inputs for classification discarding either range or explicit Doppler information, range-Doppler-surface (RDS) can more fully represent the information contained in the observed activities. However, because the data are collected from different activities, people, and locations, the RDS has a requires non-trivial adjustments for pre-processing as discussed in this paper to maintain the number of points in the RDS to fixed integer. Although it has improved performance (92%) compared to CNN (90%), this algorithm also discards phase information as most algorithms do in HAR with radar. In contrast, the phase information of the range-Doppler domain, although its performance was not the best (88%), it had no obvious weakness in the recognition of all the movements. Our proposed complex field-based fusion network (CFFN) combines the amplitude and phase which improves both the accuracy of classification (94%) as well as accelerating training time by 12.5%.

关键词： Doppler radar learning (artificial intelligence) radar target recognition radar imaging feature extraction object detection image classification image fusion

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Upgrade of the Ball and Plate Laboratory Model 16th

Upgrade of the Ball and Plate Laboratory Model

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16th International-Federation-of-Automatic-Control (IFAC) conference on Programmable Devices and Embedded systems PDES

作者： Brezina, Adam Tkacik, Milan Tkacik, Tomas Jadlovska, Slavka Tech Univ Kosice Fac Elect Engn & Informat Dept Cybernet & Artificial Intelligence Letna 9 Kosice 04200 Slovakia

This paper deals with the overall hardware and software upgrade of the Ball&Plate laboratory model used at the Center of Modern Control Techniques and Industrial Informatics (CMCT&II) at Department of Cybernetics and Artificial Intelligence (DCAI), FEEI, TUKE. Reasons for upgrading the model are described, along with the proposed solution. Design and construction of new control hardware for the model is presented. The paper next describes the implementation of program modules for controlling the position of the ball on the plate at level of the MicroController Unit (MCU) and the supervisor computer. Several approaches of image recognition with the purpose to obtain ball position are tested and compared. Finally, the paper presents the model-based design and verification of a PSD control algorithm for the Ball&Plate model. After the upgrade, the model can be used at the CMCTSLII for both research and teaching purposes, with the emphasis on the implementation of applications with high demands on hardware performance, where higher sampling rates of the control algorithms are required. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Cyber-physical systems Electronic design Embedded systems image processing Unstable system Computer vision

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Multi-frame super-resolution utilizing spatially adaptive regularization for ToF camera 17

Multi-frame super-resolution utilizing spatially adaptive re...

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17th image processing: algorithms and systems conference, IPAS 2019

作者： Lee, Haegeun Kim, Jonghyun Han, Jaeduk Kang, Moon G.I. School of Electrical and Electronic Engineering Yonsei University 50 Yonsei-ro Seodaemun-gu Seoul03722 Korea Republic of

Recently, 3D time-of-flight cameras have been developed. The development enables utilization of depth images in various fields. However, acquired depth images are corrupted by noise during the image acquisition process and have relatively lower resolution than RGB images due to the limitation of ToF cameras. In this paper, a multi-frame super-resolution reconstruction algorithm is proposed for ToF depth images to overcome such limits. The purpose of the multi-frame super-resolution reconstruction is to reconstruct a high-resolution image from observed multiple low-resolution images through the sequential process of subpixel estimation and restoration. A conventional regularized super-resolution reconstruction algorithm which takes Tikhonov regularization has a major drawback of over-smoothing around edges. To overcome the disadvantage, the spatially adaptive regularization is suggested for preservation of edges. Experimental results show that the image reconstructed by the proposed super-resolution reconstruction algorithm contains significantly higher resolution with less amount of noise and sharper edges than the observed data. © 2019, Society for Imaging Science and Technology.

关键词： image acquisition

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Real-time Human Corneal images processing Analysis of Placido Disk Corneal Topography Using Extenics 7

Real-time Human Corneal Images Processing Analysis of Placid...

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7th International conference on Information Technology and Quantitative Management (ITQM) - Information Technology and Quantitative Management Based on Artificial Intelligence

作者： Gao, Nan Du, Yuxuan Zhao, Yanwei Zhejiang Univ Technol Comp Sci & Technol Hangzhou 310023 Peoples R China Zhejiang Univ Technol Coll Mech Engn Hangzhou 310014 Peoples R China

A sub-pixel image edge detection method based on polar coordinates is proposed in order to accurately detect images obtained from corneal topographic instrument based on Placido disk. The corneal image obtained by the corneal topographic instrument has the following characteristics: 1. Real time. The image acquisition video is set to 30 frames/sec, so the image processing algorithm should have the millisecond level of computing performance;2. Quality is not stable. Because of the influence of photographing environment, machine and human entry factors, the images of cornea will have various kinds of noises. So we should propose a stable and effective preprocessing algorithm. 3. image offset. Due to the operation characteristics of such corneal topographic system, the consecutive images' centers are unavoidable drifted during the process of image acquisition. So it is necessary to match the same serial target pictures. According to the above characteristics, based on the theory of extension and matter-element data structure, this paper efficiently structured captured images and uses two-dimensional Gaussian smoothing function to preprocess the data of all kinds of noises, including real human eyelashes removing and uses mixed Canbel (combining the canny and Sobel algorithms) and regional three-polynomial fitting method to effectively detect the sub-pixel edges of corneal images which we derive. Based on the experiments of standard simulation eye and real human eye, it is proved that the algorithm presented in this paper has good robustness and detection accuracy (the refractive error distributions of standard simulation eyes with different curvatures are less than 0.25D), which meets the operation requirements of actual systems used in industry. So our algorithm can be used in such corneal topographer in order to help detection of various eye diseases. (C) 2020 The Authors. Published by Elsevier B.V.

关键词： corneal topography image de-noising sub-pixel edge detection extenics matter-element analysis

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CoMIR: contrastive multimodal image representation for registration 20

CoMIR: contrastive multimodal image representation for regis...

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Proceedings of the 34th International conference on Neural Information processing systems

作者： Nicolas Pielawski Elisabeth Wetzer Johan Öfverstedt Jiahao Lu Carolina Wählby Joakim Lindblad Nataša Sladoje Dept. of Information Technology Uppsala University Sweden

ISBN: (纸本)9781713829546

We propose contrastive coding to learn shared, dense image representations, referred to as CoMIRs (Contrastive Multimodal image Representations). CoMIRs enable the registration of multimodal images where existing registration methods often fail due to a lack of sufficiently similar image structures. CoMIRs reduce the multimodal registration problem to a monomodal one, in which general intensity-based, as well as feature-based, registration algorithms can be applied. The method involves training one neural network per modality on aligned images, using a contrastive loss based on noise-contrastive estimation (InfoNCE). Unlike other contrastive coding methods, used for, e.g., classification, our approach generates image-like representations that contain the information shared between modalities. We introduce a novel, hyperparameter-free modification to InfoNCE, to enforce rotational equivariance of the learnt representations, a property essential to the registration task. We assess the extent of achieved rotational equivariance and the stability of the representations with respect to weight initialization, training set, and hyperparameter settings, on a remote sensing dataset of RGB and near-infrared images. We evaluate the learnt representations through registration of a biomedical dataset of bright-field and second-harmonic generation microscopy images; two modalities with very little apparent correlation. The proposed approach based on CoMIRs significantly outperforms registration of representations created by GAN-based image-to-image translation, as well as a state-of-the-art, application-specific method which takes additional knowledge about the data into account.

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