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IEEE Computer Society conference on Computer vision and Pattern Recognition Workshops (CvPRW)

作者： Md Rifat Arefin vincent Michalski Pierre-Luc St-Charles Alfredo Kalaitzis Sookyung Kim Samira E. Kahou Yoshua Bengio Mila - Quebec AI Institute Element AI Lawrence Livermore National Laboratory

ISBN: (数字)9781728193601

ISBN: (纸本)9781728193618

High-resolution satellite imagery is critical for various earth observation applications related to environment monitoring, geoscience, forecasting, and land use analysis. However, the acquisition cost of such high-quality imagery due to the scarcity of providers and needs for high-frequency revisits restricts its accessibility in many fields. In this work, we present a data-driven, multi-image super resolution approach to alleviate these problems. Our approach is based on an end-to-end deep neural network that consists of an encoder, a fusion module, and a decoder. The encoder extracts co-registered highly efficient feature representations from low-resolution images of a scene. A Gated Re-current Unit (GRU)-based module acts as the fusion module, aggregating features into a combined representation. Finally, a decoder reconstructs the super-resolved image. The proposed model is evaluated on the PROBA-v dataset released in a recent competition held by the European Space Agency. Our results show that it performs among the top contenders and offers a new practical solution for real-world applications.

关键词： image resolution image reconstruction Satellites Machine learning Decoding Remote sensing Earth

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data-fitting reconstruction for Defect Inspection of Airplane Aluminum Structure in Infrared Thermographic NDT

Data-fitting Reconstruction for Defect Inspection of Airplan...

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IEEE conference on Industrial Electronics and Applications (ICIEA)

作者： Kai Wan Qishuang Ma School of Automation Science and Electrical Engineering Beijing University of Aeronautics and Astronautics Beijing China

ISBN: (纸本)9781424427994

Infrared (IR) thermography has already demonstrated to be an effective tool for nondestructive testing and evaluation (NDT&E) applications. Pulsed thermography (PT) is such kind of technique often used in rapid and wide-area subsurface inspection. In aviation industry, metal structures of aluminum, which has high thermal conductivity and diffusivity, usually need to be verified in material integrality both for manufacture and maintenance. And it is generally difficult to get sufficient noise-free sampling data for an accurate analysis due to swift heat conduction in material of high thermal conductivity, if the IR device is not good enough for a high sampling rate. So a data-fitting process is offered to reconstruct the sequence from a PT test for cost-effective detection by a commercial mediocre infrared imaging system. This method brings two evident advantages: increased image quality by reducing temporal stochastic noise, and discretionary number of reconstructed frame at any precision for quantitative analysis. A particular specimen of duralumin is machined to emulate airplane components. And experimental difference curves and images are given, behaving well to indicate the validity of this economical inspection.

关键词： Thermography NDT data-fitting

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image-Based Target Tracking Using Least-Squares Trajectory Estimation without A Priori Knowledge

Image-Based Target Tracking Using Least-Squares Trajectory E...

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IEEE Aerospace conference

作者： Timothy D. Matchen Brett R. Nadler Department of Mechanical and Aerospace Engineering Princeton University Princeton NJ 08544 862-216-4246 Space Instrument Realization Intelligence and Space Research Los Alamos National Laboratory Los Alamos NM 87545 505-667-5644

ISBN: (纸本)9781479916191

Accurate object tracking has become increasingly important with developments in Lidar and high-resolution camera systems for remote surveillance. Typical methods utilize Markov Chain state estimation paired with Kalman or particle filters. These methods, however, are susceptible to loss of track if an error is encountered or a loss of image occurs. We developed a set of algorithms built on more recent efforts that have been aimed at reconstructing the three-dimensional trajectory of the object. These methods typically require a priori information about the target being tracked when using a single camera. We attempt to accomplish trajectory reconstruction without information about the system beyond a known camera matrix. Using feature locations extracted from a series of images combined with the associated camera matrices, we generate a linear system of equations relating the image coordinates in two-dimensional projective space to the real-world three-dimensional coordinates. We use this system of equations to generate a least-squares polynomial fit for the data. The resulting system of equations successfully recovers polynomial equations of motion and outperforms Taylor approximations of equal degree outside of the convergent region. Introducing translational errors causes the error-minimizing angle combination to differ from the single most likely analytic angle combination. We employ a mean-approximating method to generate an adjusted angular value and demonstrate this represents an improvement in accuracy over the analytic solution.

关键词： demonstrate solution generate

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3D trajectories re-construction of droplets ejected in controlled tungsten melting studies in ASDEX Upgrade

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JOURNAL OF NUCLEAR MATERIALS 2013年第sup期438卷 S846-S851页

作者： Yang, Zhongshi Krieger, K. Lunt, T. Brochard, F. Briancon, J. -L. Neu, R. Dux, R. Janzer, A. Potzel, S. Puetterich, T. Max Planck Inst Plasma Phys EURATOM Assoziat D-85748 Garching Germany Chinese Acad Sci Inst Plasma Phys Hefei 230031 Peoples R China Univ Lorraine Inst Jean Lamour F-54506 Vandoeuvre Les Nancy France

Two fast visible range camera systems with vertically and tangentially oriented crossed viewing fields in the divertor region of ASDEX Upgrade were used to observe tungsten (W) droplets ejected from a melting W-pin into the divertor plasma. To obtain the spatial (3D) trajectories of the tungsten droplets, the trajectory of a given droplet in the (2D) camera image coordinate system was derived for each view separately. from these data, the 3D droplet position was derived by computing the shortest line segment connecting crossed viewing chords to a given droplet taking the centre coordinate of the line segment as actual coordinate. The experimental error of the derived position was estimated from the length of the connecting line segment. In the toroidal direction, the computed trajectories can be described by an analytical transport model for the droplets assuming an initial droplet diameter in the range of 60100 mu m. In the vertical direction the vertical distance droplets travelled when reaching the edge of the viewing field also agrees with the model predictions. However, discrepancies are found with respect to the time point whence a droplet reverts its initial downwards motion due to centrifugal forces exceeding gravity and plasma generated force components. (C) 2013 Elsevier B. v. All rights reserved.

关键词： TRAJECTORIES (Mechanics) MELTING points image reconstruction THREE-dimensional imaging image processing NUCLEAR physics experiments

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Frequency-Diverse Computational Polarimetic Imaging

Frequency-Diverse Computational Polarimetic Imaging

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European conference on Antennas and Propagation

作者： Okan Yurduseven Thomas fromenteze Rixi Peng David R. Smith School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast United Kingdom XLIM UMR 7252 Université de Limoges/CNRS Limoges France Department of Electrical and Computer Engineering Duke University Durham NC

In this paper, a frequency-diverse computational polarimetric imaging system is demonstrated at K-band (17.5-26.5 GHz) frequencies. The frequency-diverse operation enables all-electronic data-acquisition by means of a simple frequency-sweep and requires no mechanically moving apparatus or phase shifting circuits for imaging. Leveraging a tensor model for the scattering behavior, as opposed to a scalar model, enables the extraction of further information from the imaged objects. This is shown by means of frequency-diverse polarimetric imaging of complex objects, such as the letters of the word "DUKE", and comparing the reconstructed polarimetric images to the reflectivity-only reconstructions of the same objects.

关键词： Cavity resonators Frequency measurement Antenna measurements Microwave imaging Apertures image reconstruction

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MIPI 2022 Challenge on Under-Display Camera image Restoration: Methods and Results 17th

MIPI 2022 Challenge on Under-Display Camera Image Restorati...

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17th European conference on Computer vision, ECCv 2022

作者： Feng, Ruicheng Li, Chongyi Zhou, Shangchen Sun, Wenxiu Zhu, Qingpeng Jiang, Jun Yang, Qingyu Loy, Chen Change Gu, Jinwei Zhu, Yurui Wang, Xi Fu, Xueyang Hu, Xiaowei Hu, Jinfan Liu, Xina Chen, Xiangyu Dong, Chao Zhang, Dafeng Huang, Feiyu Liu, Shizhuo Wang, Xiaobing Jin, Zhezhu Jiang, Xuhao Shao, Guangqi Wang, Xiaotao Lei, Lei Zhang, Zhao Zhao, Suiyi Zheng, Huan Gao, Yangcheng Wei, Yanyan Ren, Jiahuan Huang, Tao Fang, Zhenxuan Huang, Mengluan Xu, Junwei Zhang, Yong Yang, Yuechi Shu, Qidi Yang, Zhiwen Li, Shaocong Yao, Mingde Xu, Ruikang Guan, Yuanshen Huang, Jie Xiong, Zhiwei Zhu, Hangyan Liu, Ming Liu, Shaohui Zuo, Wangmeng Jia, Zhuang Song, Binbin Song, Ziqi Mao, Guiting Hou, Ben Liu, Zhimou Ke, Yi Ouyang, Dengpei Han, Dekui Zhang, Jinghao Zhu, Qi Zheng, Naishan Zhao, Feng Jin, Wu Conde, Marcos Nathan, Sabari Timofte, Radu Xu, Tianyi Xu, Jun Hrishikesh, P.S. Puthussery, Densen Jiji, C.v. Jiang, Biao Ding, Yuhan Li, WanZhang Feng, Xiaoyue Chen, Sijing Zhong, Tianheng Lu, Jiyang Chen, Hongming Fan, Zhentao Chen, Xiang Nanyang Technological University Singapore Singapore SenseBrain San Jose United States Shanghai AI Laboratory Shanghai China SenseTime Research and Tetras.AI Beijing China University of Science and Technology of China Hefei China Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Samsung Research China Beijing China Xiaomi Beijing China Hefei University of Technology Hefei China School of Artificial Intelligence Xidian University Xi’an China School of Remote Sensing and Information Engineering Wuhan University Wuhan China State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing Wuhan University Wuhan China Harbin Institute of Technology Harbin China University of Macau China Changsha Research Institute of Mining and Metallurgy Changsha China Tianjin University Tianjin China Computer Vision Lab University of Wurzburg Würzburg Germany Couger Inc. Tokyo Japan School of Statistics and Data Science Nankai University Tianjin China Founding Minds Software Thiruvananthapuram India Department of Electronics and Communication SRM University AP Amaravati India Fudan University Shanghai China Shenyang Aerospace University Shenyang China Nanjing University of Science and Technology Nanjing China

ISBN: (纸本)9783031250712

Developing and integrating advanced image sensors with novel algorithms in camera systems is prevalent with the increasing demand for computational photography and imaging on mobile platforms. However, the lack of high-quality data for research and the rare opportunity for in-depth exchange of views from industry and academia constrain the development of mobile intelligent photography and imaging (MIPI). To bridge the gap, we introduce the first MIPI challenge including five tracks focusing on novel image sensors and imaging algorithms. In this paper, we summarize and review the Under-Display Camera (UDC) image Restoration track on MIPI 2022. In total, 167 participants were successfully registered, and 19 teams submitted results in the final testing phase. The developed solutions in this challenge achieved state-of-the-art performance on Under-Display Camera image Restoration. A detailed description of all models developed in this challenge is provided in this paper. More details of this challenge and the link to the dataset can be found at https://***/mipi-challenge/MIPI2022. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： image reconstruction

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Graph Attention Convolutional Network for 3D Human Pose and Shape Estimation from Point Clouds

Graph Attention Convolutional Network for 3D Human Pose and ...

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IEEE International conference on Multimedia and Expo (ICME)

作者： Yung-Wei Fan Sheng-Chun Huang Shao-Yi Chien National Taiwan University

ISBN: (数字)9798350390155

ISBN: (纸本)9798350390162

We propose Graph Attention Convolutional Network for 3D human pose and shape estimation. Unlike most deep-learning methods that utilize RGB images as input, we opt for 3D data, believing it can convey richer information. Our method comprises two-stage models. The first, named the Local Joint Network (LJN), employs grouping techniques to gather points and predict 3D joints. The second is Graph Attention Convolutional Network, which takes 3D joints as input, leveraging a combination of Graph Convolutional Neural Networks (GC-NNs) and Transformers. The key advantage lies in its consideration of both local and non-local interactions. We acquire point clouds using synthetic data and a Kinect v2 camera. Additionally, for RGB images lacking 3D information, we introduce a Point Cloud Generation System capable of synthesizing 3D data. To the best of our knowledge, we are the first to apply this mechanism to this field.

关键词： Point cloud compression Three-dimensional displays Shape Estimation Transformers Cameras data models Convolutional neural networks image reconstruction Synthetic data

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Effect of normalization method on image uniformity and binding potential estimates on microPET

Effect of normalization method on image uniformity and bindi...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： M.-L. Camborde A. Rhamim D.F. Newport S. Siegel K.R. Buckley E. vandervoort T.J. Ruth v. Sossi University of British Columbia Vancouver BC Canada CTI Concorde MicroSystems LLC Knoxville TN USA TRIUMF Vancouver BC Canada

This study investigates different detector normalization procedures for a small animal scanner, specifically the Concorde microPET/sup /spl reg// R4. The procedures were compared in terms of: (i) image uniformity, (ii) performance as a function of count rate, and (iii) impact on the estimate of the binding potential (BP) in brain rat studies. image uniformity studies were performed on two cylindrical phantoms of different size filled with an aqueous concentration of /sup 11/C (38 kBq/mL and 615 kBq/mL). BP was estimated with the Logan graphical approach on 12 /sup 11/C-Methylphenidate and 9 /sup 11/C-Dihydrotetrabenazine rat studies processed with all the normalization procedures. We found that: 1) the combination, the geometry normalized combination, the component-point, and the geometry normalized component procedures significantly improve radial image uniformity compared to the direct-point and direct-cylinder procedures, 2) the geometry normalized combination procedure seems to provide the best radial and axial uniformity, 3) a mismatch between the count rates at which the normalization and the emission scans are acquired degrades the axial uniformity by 47% to 98% whereas this effect was not observed for radial uniformity, and 4) the difference in BP values obtained from data corrected with different normalization procedures is as high as 15% for normal striatum and 75% for lesion striatum.

关键词： Detectors Positron emission tomography Geometry Animals Humans Imaging phantoms Degradation Lesions image reconstruction Frequency

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Matrix Completion Based ECG Compression

Matrix Completion Based ECG Compression

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Annual International conference of the IEEE Engineering in Medicine and Biology Society

作者： Luisa F. Polania Rafael E. Carrillo Manuel Blanco-velasco Kenneth E. Barner Dept. of Electrical and Computer Engineering University of Delaware Dept. Teorfa de la Senal y Comunicaciones Universidad de Alcala

ISBN: (纸本)9781424441211

An innovative electrocardiogram compression algorithm is presented in this paper. The proposed method is based on matrix completion, a new paradigm in signal processing that seeks to recover a low-rank matrix based on a small number of observations. The low-rank matrix is obtained via normalization of electrocardiogram records. Using matrix completion, the ECG data matrix is recovered from a few number of entries, thereby yielding high compression ratios comparable to those obtained by existing compression techniques. The proposed scheme offers a low-complexity encoder, good tolerance to quantization noise, and good quality reconstruction.

关键词： Electrocardiography Heart beat image coding Decoding Wavelet transforms Noise

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Design of the First Neuronal Connectomics Challenge: from Imaging to Connectivity

Design of the First Neuronal Connectomics Challenge: From Im...

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International Joint conference on Neural Networks

作者： Isabelle Guyon Demian Battaglia Alice Guyon vincent Lemaire Javier G. Orlandi Bisakha Ray Mehreen Saeed Jordi Soriano Alexander Statnikov Olav Stetter ChaLearn University of Marseille CNRS Sophia Antipolis Orange University of Barcelona New York University FAST National University of Computer and Emerging Sciences of Pakistan Max Planck Institute for Dynamics and Self-Organization

ISBN: (纸本)9781479914821

We are organizing a challenge to reverse engineer the structure of neuronal networks from patterns of activity recorded with calcium fluorescence imaging. Unraveling the brain structure at the neuronal level at a large scale is an important step in brain science, with many ramifications in the comprehension of animal and human intelligence and learning capabilities, as well as understanding and curing neuronal diseases and injuries. However, uncovering the anatomy of the brain by disentangling the neural wiring with its very fine and intertwined dendrites and axons, making both local and far reaching synapses, is a very arduous task: traditional methods of axonal tracing are tedious, difficult, and time consuming. This challenge proposes to approach the problem from a different angle, by reconstructing the effective connectivity of a neuronal network from observations of neuronal activity of thousands of neurons, which can be obtained with state-of-the-art fluorescence calcium imaging. To evaluate the effectiveness of proposed algorithms, we will use data obtained with a realistic simulator of real neurons for which we have ground truth of the neuronal connections. We produced simulated calcium imaging data, taking into account a model of fluorescence and light scattering. The task of the participants is to reconstruct a network of 1000 neurons from time series of neuronal activities obtained with this model. This challenge is part of the official selection of the WCCI 2014 competition program.

关键词： Neurons image reconstruction Biological neural networks Imaging Calcium data models Awards activities

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