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

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Indoor Positioning Using Smartphone Camera

Indoor Positioning Using Smartphone Camera

引用

International conference on Indoor Positioning and Indoor Navigation (IPIN)

作者： Werner, Martin Kessel, Moritz Marouane, Chadly Univ Munich Mobile & Distributed Syst Grp Munich Germany Ludwig Maximilians Univ Munchen Munich Germany

ISBN: (纸本)9781457718045

With the increasing computational power of mobile devices and the increase in the usage of ordinary location-based services, the area of indoor location-based services is of growing interest. Nowadays indoor location-based services are used mainly for personalized information retrieval of maps and points of interest. Advanced location-based functionality often suffers from imprecise positioning methods. In this paper we present a simple, yet powerful positioning method inside buildings which allows for a fine-grained detection of the position and orientation of a user while being easy to deploy and optimize. The main contribution of this paper consists of the combination of an image recognition system with a distance estimation algorithm to gain a high-quality positioning service independent from any infrastructure using the camera of a mobile device. Moreover this type of positioning can be operated in a user-contributed way and is less susceptible to small changes in the environment as compared to popular WLAN-based systems. As an extension, we propose the usage of very coarse WLAN positioning to reduce the size of the candidate set of image recognition and hence speed up the system.

关键词： Indoor Navigation image processing Location-based Services

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A parallel impulse-noise detection algorithm based on ensemble learning for switching median filters

A parallel impulse-noise detection algorithm based on ensemb...

引用

conference on parallel processing for Imaging Applications

作者： Duan, Fei Zhang, Yu-Jin Tsinghua Univ Dept Elect Engn Beijing 100084 Peoples R China

ISBN: (纸本)9780819484093

In this paper, a highly effective and efficient ensemble learning based parallel impulse noise detection algorithm is proposed. The contribution of this paper is three-fold. First, we propose a novel intensity homogeneity metric-Directional Homogeneity Descriptor(DHD), which has very powerful discriminative ability and has been proven in our previous work. 1 Second, this proposed algorithm has high parallelism in feature extraction stage, classifier training, and testing stage. And the proposed architecture are very suitable for distributed processing. Finally, instead of manually tune the thresholds for each feature as most of the works in this research area do, we use Random Forest to make decision since it has been demonstrated to own better generalization ability and performance comparable to SVM or Boosting in classification problem. Another important reason we adopt Random Forest is that it has natural parallelism structure and very significant performance advantage (e. g. the overhead of training and testing the model is very low) over other popular classifiers e. g. SVM or Boosting. To the best of our knowledge, this is the first time ensemble learning strategies have been used in the area of switching median filtering. Extensive simulations are carried out on several most common standard testing images. The experimental results show that our algorithm achieves zero miss detection results while keeping the false alarm rate at a rather low level and has great superiority over other state-of-the-art methods.

关键词： Impulse noise salt-and-pepper noise noise detection switching median filter ensemble learning random forests

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Proceedings of the 2011 International conference on High Performance Computing and Simulation, HPCS 2011

Proceedings of the 2011 International Conference on High Per...

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2011 International conference on High Performance Computing and Simulation, HPCS 2011

ISBN: (纸本)9781612843810

The proceedings contain 114 papers. The topics discussed include: dynamic placement of virtual machines for cost optimization in multi-cloud environments;machines, methods and music: on the evolution of e-research;parallel and distributed simulation from many cores to the public cloud;exploiting concurrent kernel execution on graphic processing units;parallelization of the functional flow algorithm for prediction of protein function using protein-protein interaction networks;towards self-caring MapReduce: proactively reducing fault-induced execution-time penalties;linear programming based parallel job scheduling for power constrained systems;improved real-time scheduling for periodic tasks on multiprocessors;task scheduling strategies for dynamic reconfigurable processors in distributed systems;a hybrid scheduling technique for grid workflows in advance reservation environments;and meeting deadlines within object-oriented systems.

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Measuring BRDF using a single still digital camera

Measuring BRDF using a single still digital camera

引用

International conference on Optical Instruments and Technology (OIT) - Optoelectronic Imaging and processing Technology

作者： Xiong Hanwei Xu Jun Wang Jinming Guangdong Univ Technol Guangzhou Higher Educ Mega Ctr Fac Electromech Engn Guangzhou Guangdong Peoples R China

ISBN: (纸本)9780819488411

BRDF (Bidirectional Reflective Distribution Function) is broadly used in many fields, such as physics, heat transformation, remote sensing, and computer graphics. Traditional methods to measure BRDF are expensive for most peoples, and image based approach becomes a novel direction. Until now, for such an image based system, at least a video camera and a still camera are indispensible, and the operations are not easily carried out under a convenient condition. In this paper, a method using only one still camera is proposed, with the help of a light source, a cylinder support, and a sphere. The material to be measured is painted on the sphere, putting on the cylinder support painted with BRDF-known material. Around the cylinder support, a simple control points nets are distributed. In the measurement process, the light source and the support are fixed, operators goes around the sphere to obtain pictures at different view angles and the rest work is finished automatically by a set of programs. The pictures are first processed by a photogrammetric program to get the geometry in the scene, including the positions, directions, and the shapes of light source, the support, the sphere, and the cameras. The BRDF samples are calculated from the image intensity and the obtained geometric relations, which are approximated by a multivariable spline to get a full BRDF description. Three different materials are tested with the method.

关键词： BRDF (Bidirectional Reflective Distribution Function) image-based Method

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On Sensor Selection in Linked Information Networks

On Sensor Selection in Linked Information Networks

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7th IEEE International conference on distributed Computing in Sensor Systems (DCOSS)

作者： Aggarwal, Charu C. Bar-Noy, Amotz Shamoun, Simon IBM TJ Watson Res Ctr Yorktown Hts NY 10598 USA CUNY Grad Ctr New York NY 10010 USA

ISBN: (纸本)9781457705137

Sensor networks are often redundant by design in order to achieve reliability in information processing. In many cases, the relationships between the different sensors are known a-priori, and can be represented as virtual linkages among the different sensors. These virtual linkages correspond to an information network of sensors, which provides useful external input to the problem of sensor selection. In this paper, we propose the unique approach of using external linkage information in order to improve the efficiency of very large scale sensor selection. We design efficient theoretical models, including a greedy approximation algorithm and an integer programming formulation for sensor selection. Our greedy selection algorithm provides an approximation bound of (e-1)/(2.e-1), where e is the base of the natural logarithm. We show that our approach is much more effective than baseline sampling strategies. We present experimental results that illustrate the effectiveness and efficiency of our approach.

关键词： Algorithm design and analysis Approximation algorithms Approximation methods Junctions Linear programming Minimization Prediction algorithms approximation bound approximation theory external linkage information greedy algorithms greedy approximation algor

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Lempel-Ziv Data Compression on parallel and distributed Systems

Lempel-Ziv Data Compression on Parallel and Distributed Syst...

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International conference on Data Compression, Communications and processing

作者： Sergio De Agostino Computer Science Department Sapienza University Rome Italy

We present a survey of results concerning Lempel-Ziv data compression on parallel and distributed systems, starting from the theoretical approach to parallel time complexity to conclude with the practical goal of designing distributed algorithms with low communication cost. An extension by Storer to image compression is also discussed.

关键词： Dictionaries Program processors Vegetation Complexity theory Decoding distributed algorithms image coding

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ParXII: Optimized, data-parallel exemplar-based image inpainting 11

ParXII: Optimized, data-parallel exemplar-based image inpain...

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ACM Special Interest Group on Computer Graphics and Interactive Techniques conference, SIGGRAPH'11

作者： Yousef, Mohamed Hussien, Khaled F. Assiut University Assiut Egypt

ISBN: (纸本)9781450309714

Completing unknown parts of a damaged input image, or removing objects from photographs and replacing them with visually plausible backgrounds is an important task in photo editing and video processing with a wide range of applications from the reconstruction of missing blocks introduced by packet loss during wireless transmission, reversing of impairments, removal of image objects such as logos, stamped dates, text, and persons, to completing panoramas. The problem with most of existing inpainting methods is the balance between efficiency and accuracy, one of the most accurate methods is exemplar-based image inpainting [Criminisi, et al. 2004], the problem with this method is that it's very slow and inefficient due to the fact that it needs to scan the whole image before inpaiting a certain block of pixels (every scan operation is called a query), this makes the algorithm take tens to hundreds of seconds on modern CPUs.

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Optimization of multi-level selection procedure and applications in optimization the structure of parallel and distributed systems

Optimization of multi-level selection procedure and applicat...

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IASTED International conference on Applied Simulation and Modelling, ASM 2011

作者： Riismaa, Tiit Institute of Cybernetics Tallinn University of Technology Akadeemia tee 21 12618 Tallinn Estonia

ISBN: (纸本)9780889868939

A method of description and optimization of the structure of multi-level selection procedure is presented. This procedure is a special case of a multi-level processing system. For general case the set of feasible structures for such class of systems is defined. The representation of this set is constructed in terms of the graph theory. For the reduced statement two types of variable parameters are defined: for the level size and for the relations of adjacent levels. A class of iteration methods is developed. Also a numerical method of local searching is developed. On each step of the iteration the calculation of the value of objective function is required only on some vertices of some kind of unit cube.

关键词： Mathematical programming

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GPGPU Acceleration of Cellular Simultaneous Recurrent Networks Adapted for Maze Traversals

GPGPU Acceleration of Cellular Simultaneous Recurrent Networ...

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International Joint conference on Neural Networks (IJCNN)

作者： Rice, Kenneth L. Taha, Tarek M. Iftekharuddin, Khan M. Anderson, Keith Salan, Teddy Clemson Univ Clemson SC 29634 USA Univ Dayton Dayton OH 45469 USA Memphis Univ Memphis TN 38152 USA

ISBN: (纸本)9781424496365

At present, a major initiative in the research community is investigating new ways of processing data that capture the efficiency of the human brain in hardware and software. This has resulted in increased interest and development of bio-inspired computing approaches in software and hardware. One such bio-inspired approach is Cellular Simultaneous Recurrent Networks (CSRNs). CSRNs have been demonstrated to be very useful in solving state transition type problems, such as maze traversals. Although powerful in image processing capabilities, CSRNs have high computational demands with increasing input problem size. In this work, we revisit the maze traversal problem to gain an understanding of the general processing of CSRNs. We use a 2.67 GHz Intel Xeon X5550 processor coupled with an NVIDIA Tesla C2050 general purpose graphical processing unit (GPGPU) to create several novel accelerated CSRN implementations as a means of overcoming the high computational cost. Additionally, we explore the use of decoupled extended Kalman filters in the CSRN training phase and find a significant reduction in runtime with negligible change in accuracy. We find in our results that we can achieve average speedups of 21.73 and 3.55 times for the training and testing phases respectively when compared to optimized C implementations. The main bottleneck in training performance was a matrix inversion computation. Therefore, we utilize several methods to reduce the effects of the matrix inversion computation.

关键词： Acceleration Computer architecture GPGPU acceleration Intel Xeon X5550 processor Kalman filters Microprocessors NVIDIA Tesla C2050 parallel processing Runtime Testing Training bioinspired computing cellular neural nets cellular simultaneous recurrent networks extended Kalman filters frequency 2.67 GHz general purpose graphical processing unit image processing image processing matrix inversion matrix inversion maze traversals recurrent neural nets

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parallel outlier detection using KD-tree based on MapReduce

Parallel outlier detection using KD-tree based on MapReduce

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2011 3rd IEEE International conference on Cloud Computing Technology and Science, CloudCom 2011

作者： He, Qing Ma, Yunlong Wang, Qun Zhuang, Fuzhen Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769546223

distributed and parallel algorithms have attracted a vast amount of interest and research in recent decades, to handle large-scale data set in real-world applications. In this paper, we focus on a parallel implementation of KD-Tree based outlier detection method to deal with large-scale data set. As one of the state-of-the-art outlier detection methods, KD-Tree based has been approved to be an effective algorithm. However, it still cannot process large-scale data set efficiently due to its serial implementation. Based on the current and powerful parallel programming framework - MapReduce, we propose to implement the parallel KD-Tree based outlier detection algorithm (e.g., PKDTree for short). Experimental results demonstrate the efficiency of PKDTree according to the evaluation criterions of scaleup, speedup and sizeup. © 2011 IEEE.

关键词： MapReduce

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