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检索条件"任意字段=Conference on Parallel and Distributed Methods for Image Processing III"

共 552 条记录，以下是261-270 订阅

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Robust Weighted Supervised Sparse Coding for image Classification

Robust Weighted Supervised Sparse Coding for Image Classific...

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2015 IEEE 16th International conference on Communication Technology(ICCT 2015)

作者： Xiang Zhang Naiyang Guan Zhigang Luo College of Computer National University of Defense Technology National Laboratory for Parallel and Distributed Processing National University of Defense Technology

Sparse coding has shown its great potential in learning image feature representation. Recent developed methods such as group sparse coding prefer discovering the group relationships among examples and have achieved the state-of-the-art results in image classification. However, they suffer from poor robustness shortcomings in practice. This paper proposes a robust weighted supervised sparse coding method(RWSSC) to address this ***, RWSSC distinguishes different classes' contributions to the sparse coding by a novel weighting strategy meanwhile removes the out liers by imposing1 l-regularization over the noisy entries. Benefitting from these strategies, RWSSC can effectively boost performance of sparse coding in image ***, we developed the block coordinate descent algorithm to optimize it, and proved its *** results of image classification on two popular datasets show that RWSSC outperforms the representative sparse coding methods in quantities.

关键词： Sparse coding Supervised learning image classification

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Evaluation of a Sector-Hash Based Rapid File Detection Method for Monitoring Infrastructure-as-a-Service Cloud Platforms

Evaluation of a Sector-Hash Based Rapid File Detection Metho...

引用

International conference on Availability, Reliability and Security, ARES

作者： Manabu Hirano Hayate Takase Koki Yoshida Department of Information and Computer Engineering National Institute of Technology Japan

Current computer forensics tools have some limitations on anti-forensics attacks, cloud computing, and a large increase in the size of forensics targets. To solve these problems, this paper proposes a system that preserves storage data on virtual machines by acquiring all data sectors with time stamps. The proposed system can restore a previous state of a block device at any date and time that is specified by an investigator. The proposed system aims to monitor users' behavior in Infrastructure-as-a-Service (IaaS) cloud platforms. This paper also presents a rapid file detection system that finds a target file from a large collection of the acquired data sectors by using sector-hashes and parallel distributed processing. This system enables investigators to track and to find a target file that is related to incidents or crimes in the cloud. First, this paper reports the preliminary experiments of a sector-hash based file detection method on three major operating systems for evaluating its effectiveness. We present a design and an implementation of the proposed monitoring and target file detection system by using Xen hypervisor and MapReduce. We report results of its performance evaluation. Finally, we discuss possible methods to improve the performance and the limitations of the current proposed mechanism.

关键词： Forensics Computers Monitoring image restoration distributed databases File systems Cloud computing

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Correntropy Supervised Non-negative Matrix Factorization

Correntropy Supervised Non-negative Matrix Factorization

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International Joint conference on Neural Networks

作者： Wenju Zhang Naiyang Guan Dacheng Tao Bin Mao Xuhui Huang Zhigang Luo Science and Technology on Parallel and Distributed Processing Laboratory College of Computer National University of Defense Technology Changsha Hunan China 410073 Center for Quantum Computation and Intelligent Systems FEIT University of Technology Sydney Sydney NSW 2007 Australia College of Science National University of Defense Technology Changsha Hunan China 410073 Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha Hunan China 410073

ISBN: (纸本)9781479919611

Non-negative matrix factorization (NMF) is a powerful dimension reduction method and has been widely used in many pattern recognition and computer vision problems. However, conventional NMF methods are neither robust enough as their loss functions are sensitive to outliers, nor discriminative because they completely ignore labels in a dataset. In this paper, we proposed a correntropy supervised NMF (CSNMF) to simultaneously overcome aforementioned deficiencies. In particular, CSNMF maximizes the correntropy between the data matrix and its reconstruction in low-dimensional space to inhibit outliers during learning the subspace, and narrows the minimizes the distances between coefficients of any two samples with the same class labels to enhance the subsequent classification performance. To solve CSNMF, we developed a multiplicative update rules and theoretically proved its convergence. Experimental results on popular face image datasets verify the effectiveness of CSNMF comparing with NMF, its supervised variants, and its robustified variants.

关键词： NMF subsequent classification NMF protocol matrix decomposition outliers Nonnegative LOSS FUNCTION images REDUCTION methods Dataset computer vision

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Real-time reconstruction solution for positron emission mammography imaging-guided intervention

Real-time reconstruction solution for positron emission mamm...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Xiaoyue Gu Lin Li Long Wei Mingkai Yun Wei Zhou Zhenrui Lu Leiming Shang Pengfei Ying Chinese Academy of Sciences Beijing Engineering Research Center of Radiographic Techniques and Equipment Beijing China

Positron Emission Mammography (PEM) imaging systems with the ability in detection of millimeter-sized tumors were developed in recent years. And some of them have been well used in clinical applications. In consideration of biopsy application, a double-plane PET is more practical than a ring detector for the convenience of breast immobilization. In this study, the possibility of the imaging-guided intervention under a double-plane PET was studied. The distance between the planes is changeable with different breast size. And the system matrix is computed in real-time for every plane spacing. The biopsy motivation under the double-plane PET requires a high sensitivity, great resolution performance and a quickly reconstruction speed. The sensitivity result shows the central value is 13.28% with the 6cm spacing and 200-750keV energy window. The resolution modeling method shows the resolution recovery achieved in the cross-plane. The 3D-OSEM algorithm is applied. The reconstruction is supported with GPU (GeForce GTX 660). For the GPU acceleration, both projection and back-projection procedures use the tube model. Each tube is distributed with a thread and calculated in parallel in the GPU. A double plane PET is simulated above Geant4 Application for Emission Tomography (GATE) software based on MC methods. With all the span tubes calculated, the GPU takes 19 seconds to reconstruct the image while the CPU takes 1037 seconds. The image quality was tested with different acquisition times. The series of biopsy images are showed. The point and rod source both could be imaged in the simulated biopsy process.

关键词： Graphics processing units image reconstruction Positron emission tomography Biopsy Energy resolution Real-time systems Breast

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A distributed approach for development of deformable model-based segmentation methods 5

A distributed approach for development of deformable model-b...

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5th International conference in image processing and Communications, IP&C 2013

作者： Reska, Daniel Boldak, Cezary Kretowski, Marek Bialystok University of Technology Bialystok Poland

ISBN: (纸本)9783319016214

This paper presents a distributed solution for the development of deformable model-based medical image segmentation methods. The design and implementation stages of the segmentation methods usually require a lot of time and resources, since the variations of the tested algorithms have to be constantly evaluated on many different data sets. To address this problem, we extended our web platform for development of deformable model-based methods with an ability to distribute the computational workload. The solution was implemented on a computing cluster of multi-core nodes with the use of the Java parallel processing Framework. The experimental results show significant speedup of the computations, especially in the case of resource-demanding three-dimensional methods. © Springer International Publishing Switzerland 2014.

关键词： Cluster computing

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parallel distributed Downsampled Spatio-Temporal Track-Before-Detect Algorithm 19

Parallel Distributed Downsampled Spatio-Temporal Track-Befor...

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19th International conference on methods and Models in Automation and Robotics (MMAR)

作者： Mazurek, Przemyslaw West Pomeranian Univ Technol Szczecin Dept Signal Proc & Multimedia Engn PL-71126 Szczecin Poland

ISBN: (纸本)9781479950812

Dim objects tracking, like asteroids or satellites, require high performance algorithm. Track Before Detect (TBD) algorithms could be applied for such scenario, but the computation power is very demanding. Giant amount of trajectories that could be processed is the main problem. The application of GPGPU allows the computation using optimized Downsampled Spatio Temporal TBD (ST-TBD) algorithm for small part of image sequences. Message Passing Interface (MPICH2) is applied for the image transmission and state space exchange between computers and GPGPUs. Analysis of the system with multiple processing computers, for bandwidth limited network, is provided. The system could be limited by the bandwidth of network interface, not by GPGPU, quite often. The derived formula for this system allows the design with best optimization of GPGPUs.

关键词： graphics processing units image sequences message passing object detection object tracking GPGPU MPICH2 bandwidth limited network dim object tracking downsampled spatio-temporal TBD algorithm general-purpose graphics processing unit image transmission message passing interface network interface spatio-temporal track-before-detect algorithm state-space exchange Algorithm design and analysis Computers Radar tracking Signal processing algorithms Tracking Trajectory Vectors image sequences image communication systems message passing Network interfaces Algorithm design and analysis Computers Signal processing algorithms trajectory Object detection radar target tracking tracking tracking objects Graphics processing Unit

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parallel implementation of a X-ray tomography reconstruction algorithm for high-resolution studies

Parallel implementation of a X-ray tomography reconstruction...

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13th Mediterranean conference on Medical and Biological Engineering and Computing 2013, MEDICON 2013

作者： Garcia, J. Abella, M. de Molina, C. Liria, E. Isaila, F. Carretero, J. Desco, M. Computer Architecture and Communication Area University Carlos III Madrid Spain Bioengineering and Aerospace Engineering Dept. University Carlos III Madrid Spain Madrid Spain Madrid Spain

ISBN: (纸本)9783319008455

Most small-animal X-ray computed tomography (CT) scanners are based on cone-beam geometry with a flatpanel detector orbiting in a circular trajectory. image reconstruction in these systems is usually performed by approximate methods based on the algorithm proposed by Feldkamp, Davis and Kress (FDK). Currently there is a strong need to speed-up the reconstruction of CT data in order to extend its clinical applications. The evolution of the semiconductor detector panels has resulted in an increase of detector elements density, which produces a higher amount of data to process. This work focuses on both standard and future high-resolution studies, in which multiple level of parallelism will be needed in the reconstruction process. In addition, this paper addresses the future challenges of processing high-resolution images in many-core and distributed architectures. © Springer International Publishing Switzerland 2014.

关键词： parallel architectures

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distributed non-convex ADMM-inference in large-scale random fields 25

Distributed non-convex ADMM-inference in large-scale random ...

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25th British Machine Vision conference, BMVC 2014

作者： Miksik, Ondrej Vineet, Vibhav Pérez, Patrick Torr, Philip H.S. Department of Engineering Science University of Oxford Oxford United Kingdom Technicolor Research and Innovation Cesson Sévigné France

We propose a parallel and distributed algorithm for solving discrete labeling problems in large scale random fields. Our approach is motivated by the following observations: i) very large scale image and video processing problems, such as labeling dozens of million pixels with thousands of labels, are routinely faced in many application domains;ii) the computational complexity of the current state-of-the-art inference algorithms makes them impractical to solve such large scale problems;iii) modern parallel and distributed systems provide high computation power at low cost. At the core of our algorithm is a tree-based decomposition of the original optimization problem which is solved using a non convex form of the method of alternating direction method of multipliers (ADMM). This allows efficient parallel solving of resulting sub-problems. We evaluate the efficiency and accuracy offered by our algorithm on several benchmark lowlevel vision problems, on both CPU and Nvidia GPU. We consistently achieve a factor of speed-up compared to dual decomposition (DD) approach and other ADMM-based approaches. © 2014. The copyright of this document resides with its authors.

关键词： Trees (mathematics)

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A System for Large-Scale Analysis of distributed Cameras

A System for Large-Scale Analysis of Distributed Cameras

引用

IEEE Global conference on Signal and Information processing (GlobalSIP)

作者： Kaseb, Ahmed S. Berry, Everett Koh, Youngsol Mohan, Anup Chen, Wenyi Li, He Lu, Yung-Hsiang Delp, Edward J. Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA

ISBN: (纸本)9781479970889

Thousands of cameras are connected to the Internet providing streaming data (videos or periodic images). The images contain information that can be used to determine the scene contents such as traffic, weather, and the environment. Analyzing the data from these cameras presents many challenges, such as (i) retrieving data from geographically distributed and heterogeneous cameras, (ii) providing a software environment for users to simultaneously analyze large amounts of data from the cameras, (iii) allocating and managing computation and storage resources. This paper presents a system designed to address these challenges. The system enables users to execute image analysis and computer vision techniques on a large scale with only slight changes to the existing methods. It currently includes more than 65,000 cameras deployed worldwide. Users can select cameras for the types of analysis they can do. The system allocates Amazon EC2 and Windows Azure cloud instances for executing the analysis. Our experiments demonstrate that this system can be used for a variety of image analysis techniques (e.g. motion analysis and human detection) using 2.7 million images from 1274 cameras for three hours using 15 cloud instances to analyze 141 GB of images (at 107 Mbps).

关键词： Network Camera image Analysis Big Data Cloud Computing

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Proposal of Eye-gaze Recognize Method for Input Interface without Infra-red Ray Equipment 15

Proposal of Eye-gaze Recognize Method for Input Interface wi...

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15th IEEE/ACIS International conference on Software Engineering, Artificial Intelligence, Networking and parallel/distributed Computing (SNPD)

作者： Fukushima, Kazuki Shirahama, Naruki Kitakyushu Natl Coll Technol Dept Control Engn Adv Engn Kitakyushu Fukuoka Japan Kitakyushu Natl Coll Technol Dept Elect & Control Kitakyushu Fukuoka Japan

ISBN: (纸本)9781479956043

The main purpose of this study is to develop the inexpensive eye-gaze input interface for disabled people. The eye-gaze inputting can suit many situations, and it has little load for user because it is non-contact input interface. Many projects about the eye-gaze have been studied recently. Most of the productions of eye-gaze inputting use infra-red rays (IR) to detect the iris in the eyes. However the harm of IR for human eyes has been pointed out. In addition, if the interface requires the camera which has IR, the users must purchase the specific devices. Therefore we adopted a PC and the camera doesn't have the IR function. We propose the system by using the motion-template that is one of the functions of OpenCV library for tracking motion. However this function can't recognize the point where the user watches on monitor. It can recognize only the motion. That's why we made calibrate function to relate the eye-gaze with the monitor. We propose two methods to recognize eye-gaze. Both methods require the iris binary image. This image shows the iris shape and we expect that user's visual point can be calculated from this iris image. One method uses gravity point to calculate the point. Other method uses the rectangular approximation to calculate it. We did experiments for some subjects by both methods and compared the results to validate which method is proper and how much the calibrate function is accurate. In the experiment, the function randomly spotted a blue target on the monitor. The target position changes on a regular basis. In this experiment, the user stares at the target and we check the accuracy. If this function or methods are proper, the function correctly recognizes the user stare at target or near. For more accuracy, we will consider about how to detect the iris correctly in the future.

关键词： assistive technology eye-gaze web-camera image processing welfare support-equipment OpenCV

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