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IEEE Metrology for Aerospace

作者： Sebastiano Chiodini Marco Pertile Riccardo Giubilato Federico Salvioli Marco Barrera Paola Franceschetti Stefano Debei CISAS “Giuseppe Colombo” University of Padova Padova Italy Department of Industrial Engineering University of Padova Padova Italy ALTEC S.p.A. Torino Italy Thales Alenia Space – Italia Torino Italy

During the development and testing phases of ego-motion estimation algorithms for robotics applications, such as Visual Odometry (VO) or visual SLAM, a ground truth trajectory is needed in order to evaluate their performances. Nowadays motion capture systems can reach millimetric accuracy thus they are a practical and accurate solution to give camera referencing trajectory during the acquisitions of datasets and evaluation benchmarks. In practice, it is particularly difficult to make the tracked frame coincident with the camera optical frame, thus a calibration procedure is needed to estimate this transformation and achieve the millimetric accuracy required for robotic exploration missions, like scientific site mapping, or satellite relative navigation. In this work we present a calibration procedure to estimate the transformation between the reference frame tracked by a motion capture system and the optical reference frame of a stereo camera. Moreover, we perform an uncertainty analysis of the adopted method and thanks to the experimental set-up we show its ability to reach a millimeter accuracy.

关键词： Cameras Calibration Tracking Three-dimensional displays optimization Simultaneous localization and mapping Trajectory

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Synoptic video based human crowd behavior analysis for forensic video surveillance

Synoptic video based human crowd behavior analysis for foren...

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international Conference on Advances in Pattern Recognition (ICAPR)

作者： B. Yogameena K. Sindhu Priya Thiagarajar College of Engineering Madurai Tamil Nadu IN

Modeling human blobs in crowd for analyzing the behavior is an important issue for video surveillance and is a challenging task due to the unpredictability. Huge video dataset is captured by using various resources like surveillance cameras in many places including the public environment like railway station, airport etc. It is very time consuming to watch the whole video manually for forensic applications of analysis. Most of the computer vision algorithms are concentrating for real time solutions. But, still after the fact also, so many issues could not be analyzed well. For example, if one wants to analyze a specific activity in a video, watching the video for so many hours is hectic. In this paper, Video synopsis is used to represent a short video while preserving the essential activities for a long video. In the existing methodology, active objects are shifted along the time axis and hence the video is compressed much, it causes collisions among the moving objects. Therefore, compact video synopsis is proposed by using a spatiotemporal optimization, which will shift the active object along the space as well as time and thus avoid collision among them. This synthesized compact background is introduced by using multilevel patch relocation (MPR) method to provide a larger virtual motion space for shifted objects. The synoptic video is proposed here to detect if any anomalies of human crowd(s) is present in the scene in a quicker time. Experimental results obtained by using extensive dataset show that the proposed algorithm is effective in detecting anomalous events for uncontrolled environment of video surveillance.

关键词： Spatiotemporal phenomena optimization Streaming media Video surveillance Algorithm design and analysis Forensics

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Analysis of Fluorescence Lifetime Imaging Microscopy (FLIM) Data Based on a Fully Automated Laguerre Deconvolution Method

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METHODS OF INFORMATION IN MEDICINE 2010年第5期49卷 531-536页

作者： Pande, P. Trivedi, C. A. Jo, J. A. Texas A&M Univ Dept Biomed Engn College Stn TX 77843 USA

Objectives: A novel Fluorescence Lifetime. Imaging Microscopy (FLIM) deconvolution method based on the linear expansion of fluorescence decays on a set of orthonormal Laguerre functions was recently proposed. The Laguerre deconvolution method applies linear least-square estimation to estimate the expansion coefficients of all pixel decays simultaneously, performing at least two orders of magnitude faster than the other algorithms. In the original Laguerre FLIM deconvolution implementation, however, the Laguerre parameter alpha is selected using a heuristic approach, making it unsuitable for online applications. Methods: In this study, we present a fully automated implementation of the Laguerre FLIM deconvolution, whereby the Laguerre parameter alpha is treated as a free parameter within a nonlinear lest-squares optimization scheme. Results: The performance of this method has been successfully validated on simulated data, and experimental FLIM images of standard fluorescent dyes and endogenous tissue fluorescence Conclusions: The main advantage of the proposed method is that it does not require any user intervention for tuning up the deconvolution process Thus, we believe this method will facilitate the translation of RIM to online applications, including real-time clinical diagnosis.

关键词： Fluorescence Lifetime Imaging Microscopy Laguerre deconvolution nonlinear least squares optimization

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Parallel Implementation of 2D-DWT by Purging Read after Write Dependency for High Speed applications

Parallel Implementation of 2D-DWT by Purging Read after Writ...

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international Conference on Emerging Technologies, ICET

作者： M. Ashraf M. Shamim Baig Liaqat Ali Khan Ali Hassan Center for Cyber Technology and Spectrum Management National University of Science and Technology Islamabad Pakistan Center for Cyber Technology and Spectrum Management National University of Science and Technology Islamabad

ISBN: (纸本)1424414935

This paper proposes an efficient implementation of multistage, multiple-level DSP algorithms suitable for parallel and distributed processing. To describe our method we selected Mallat's algorithm for two dimensional wavelet transforms (2D-DWT) coefficient computation which has multistage and multilevel processing requirements. We have selected field programmable gate arrays (FPGA) as a processing unit because of its inherited parallel processing capabilities but our method is not limited to FPGAs only. Our method directly computes 2D-DWT coefficients without computing and storing intermediate results; which makes it faster; resource saving and removes read after Write (RAW) dependencies. We discuss multistage and single level implementation but ideally it can be extended to n-level implementation. We also proposed method for generation of "mutually scaled filter coefficients (MSFC)" and computation of maximum number of parallel processors for optimized performance in this particular case. Both lookup tables (LUTs) and multipliers along with addition/subtraction architecture can be used. However, LUTs have advantage of high processing speed. Two computational stages are combined into a single stage to remove read after write (RAW) dependency. Our implementation takes N 2 /4+L 2 /4-2 time units to compute 2D- DWT of N x N input data, with filter length of L without intermediate storage. This method can be used for other multistage, multilevel DSP problems. Quartusreg II IDE and Altera Stratix device is used for implementation.

关键词： Field programmable gate arrays Table lookup Digital signal processing Filters Distributed processing Wavelet transforms Parallel processing Concurrent computing optimization methods Computer architecture

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Experimental Implementation of Improved P&O MPPT Algorithm based on Fuzzy Logic for Solar Photovoltaic applications

Experimental Implementation of Improved P&O MPPT Algorithm b...

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international Smart Grid workshop and Certificate Program (ISGWCP)

作者： Claude Bertin Nzoundja Fapi Hyacinthe Tchakounté Mohamed Assaad Hamida Patrice Wira Martin Kamta LS2N Laboratory Ecole Centrale de Nantes Nantes Université Nantes France IRIMAS Laboratory University of Haute Alsace Mulhouse France LESIA Laboratory ENSAI University of Ngaoundere Ngaoundere Cameroon LAMSEBP Laboratory Faculty of Science University of Yaoundé I Yaoundé Cameroon

In this work, a literature review of the maximum power point tracking (MPPT) perturb and observe (P&O) technique for photovoltaic (PV) systems is first developed. The P & O algorithms available in the literature are distributed through three groups: a modification of the basic structure of P&O method, a combination of P&O techniques with a classical technique (FSCC, FOCV, SMC) and a combination with another smart technique (FLC, ANN, PSO). Subsequently, the experimental implementation of an improved MPPT P&O algorithm based on fuzzy logic (FL) for solar PV applications is proposed. The conventional P&O algorithm is widely used in PV generation systems due to its easy implementation and low cost. Notwithstanding, its main limitation is the trade-off between dynamic response and steady state oscillation. In order to overcome the limitations existing in the implementations of the conventional P&O algorithm, a FL based controller block is used to provide a variable step. The experimental results show that the response time of the proposed technique is better than the conventional P&O technique. In addition, it is found that the power oscillations and stability of the proposed control are almost eliminated. The improved P&O control based on FLC is accurate, simple and allows a faster optimization towards the maximum power point (MPP) relative to the suggested P&O algorithms found in the literature.

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GenHap: a novel computational method based on genetic algorithms for haplotype assembly

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BMC BIOINFORMATICS 2019年第Sup4期20卷 172-172页

作者： Tangherloni, Andrea Spolaor, Simone Rundo, Leonardo Nobile, Marco S. Cazzaniga, Paolo Mauri, Giancarlo Lio, Pietro Merelli, Ivan Besozzi, Daniela Univ Milano Bicocca Dept Informat Syst & Commun DISCo Viale Sarca 336U14 Bldg I-20126 Milan Italy Univ Bergamo Dept Human & Social Sci Piazzale St Agostino 2 I-24129 Bergamo Italy Univ Cambridge Comp Lab 15 JJ Thomson Ave Cambridge CB3 0FD England Italian Natl Res Council Inst Biomed Technol Via Fratelli Cervi 93 I-20090 Segrate MI Italy Italian Natl Res Council Inst Mol Bioimaging & Physiol I-90015 Cefalu PA Italy SYSBIO IT Ctr Syst Biol Piazza Sci 2 I-20126 Milan Italy

BackgroundIn order to fully characterize the genome of an individual, the reconstruction of the two distinct copies of each chromosome, called haplotypes, is essential. The computational problem of inferring the full haplotype of a cell starting from read sequencing data is known as haplotype assembly, and consists in assigning all heterozygous Single Nucleotide Polymorphisms (SNPs) to exactly one of the two chromosomes. Indeed, the knowledge of complete haplotypes is generally more informative than analyzing single SNPs and plays a fundamental role in many medical *** reconstruct the two haplotypes, we addressed the weighted Minimum Error Correction (wMEC) problem, which is a successful approach for haplotype assembly. This NP-hard problem consists in computing the two haplotypes that partition the sequencing reads into two disjoint sub-sets, with the least number of corrections to the SNP values. To this aim, we propose here GenHap, a novel computational method for haplotype assembly based on Genetic algorithms, yielding optimal solutions by means of a global search process. In order to evaluate the effectiveness of our approach, we run GenHap on two synthetic (yet realistic) datasets, based on the Roche/454 and PacBio RS II sequencing technologies. We compared the performance of GenHap against HapCol, an efficient state-of-the-art algorithm for haplotype phasing. Our results show that GenHap always obtains high accuracy solutions (in terms of haplotype error rate), and is up to 4x faster than HapCol in the case of Roche/454 instances and up to 20x faster when compared on the PacBio RS II dataset. Finally, we assessed the performance of GenHap on two different real ***-generation sequencing technologies, producing longer reads with higher coverage, can highly benefit from GenHap, thanks to its capability of efficiently solving large instances of the haplotype assembly problem. Moreover, the optimization approach proposed i

关键词： Haplotype assembly Future-generation sequencing Genetic algorithms Combinatorial optimization Weighted minimum error correction problem

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Autotuning CUDA compiler parameters for heterogeneous applications using the OpenTuner framework

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CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE 2017年第22期29卷

作者： Bruel, Pedro Amaris, Marcos Goldman, Alfredo Univ Sao Paulo IME R Matao 1010Cidade Univ Sao Paulo SP Brazil

A Graphics Processing Unit (GPU) is a parallel computing coprocessor specialized in accelerating vector operations. The enormous heterogeneity of parallel computing platforms justifies and motivates the development of automated optimization tools and techniques. The Algorithm Selection Problem consists in finding a combination of algorithms, or a configuration of an algorithm, that optimizes the solution of a set of problem instances. An autotuner solves the Algorithm Selection Problem using search and optimization techniques. In this paper, we implement an autotuner for the Compute Unified Device Architecture compiler's parameters using the OpenTuner framework. The autotuner searches for a set of compilation parameters that optimizes the time to solve a problem. We analyze the performance speedups, in comparison with high-level compiler optimizations, achieved in three different GPU devices, for 17 heterogeneous GPU applications, 12 of which are from the Rodinia Benchmark Suite. The autotuner often beats the compiler's high-level optimizations, but underperformed for some problems. We achieved over 2x speedup for Gaussian Elimination and almost 2x speedup for Heart Wall, both problems from the Rodinia Benchmark, and over 4x speedup for a matrix multiplication algorithm. Copyright (c) 2017 John Wiley & Sons, Ltd.

关键词： autotuning GPUs compilers CUDA OpenTuner

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Vertex Reordering for Real-World Graphs and applications: An Empirical Evaluation

Vertex Reordering for Real-World Graphs and Applications: An...

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IEEE international workshop/Symposium on Workload Characterization

作者： Reet Barik Marco Minutoli Mahantesh Halappanavar Nathan R. Tallent Ananth Kalyanaraman Washington State University Pullman WA USA Pacific Northwest National Laboratory Richland WA USA

ISBN: (数字)9781728176451

ISBN: (纸本)9781728176468

Vertex reordering is a way to improve locality in graph computations. Given an input (or “natural”) order, reordering aims to compute an alternate permutation of the vertices that is aimed at maximizing a locality-based objective. Given decades of research on this topic, there are tens of graph reordering schemes, and there are also several linear arrangement “gap” measures for treatment as objectives. However, a comprehensive empirical analysis of the efficacy of the ordering schemes against the different gap measures, and against real-world applications is currently lacking. In this study, we present an extensive empirical evaluation of up to 11 ordering schemes, taken from different classes of approaches, on a set of 34 real-world graphs emerging from different application domains. Our study is presented in two parts: a) a thorough comparative evaluation of the different ordering schemes on their effectiveness to optimize different linear arrangement gap measures, relevant to preserving locality; and b) extensive evaluation of the impact of the ordering schemes on two real-world, parallel graph applications, namely, community detection and influence maximization. Our studies show a significant divergence among the ordering schemes (up to 40x between the best and the poor) in their effectiveness to reduce the gap measures; and a wide ranging impact of the ordering schemes on various aspects including application runtime (up to 4x), memory and cache use, load balancing, and parallel work and efficiency. The comparative study also helps in revealing the nuances of a parallel environment (compared to serial) on the ordering schemes and their role in optimizing applications.

关键词： Bandwidth Partitioning algorithms Runtime Tools optimization Loss measurement Load management

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Online Stochastic Tensor Decomposition for Background Subtraction in Multispectral Video Sequences

Online Stochastic Tensor Decomposition for Background Subtra...

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international Conference on Computer Vision workshops (ICCV workshops)

作者： Andrews Sobral Sajid Javed Soon Ki Jung Thierry Bouwmans El-hadi Zahzah University of La Rochelle France Kyungpook National University Korea School of Computer Science and Engineering

ISBN: (纸本)9781467397124

Background subtraction is an important task for visual surveillance systems. However, this task becomes more complex when the data size grows since the real-world scenario requires larger data to be processed in a more efficient way, and in some cases, in a continuous manner. Until now, most of background subtraction algorithms were designed for mono or trichromatic cameras within the visible spectrum or near infrared part. Recent advances in multispectral imaging technologies give the possibility to record multispectral videos for video surveillance applications. Due to the specific nature of these data, many of the bands within multispectral images are often strongly correlated. In addition, processing multispectral images with hundreds of bands can be computationally burdensome. In order to address these major difficulties of multispectral imaging for video surveillance, this paper propose an online stochastic framework for tensor decomposition of multispectral video sequences (OSTD). First, the experimental evaluations on synthetic generated data show the robustness of the OSTD with other state of the art approaches then, we apply the same idea on seven multispectral video bands to show that only RGB features are not sufficient to tackle color saturation, illumination variations and shadows problem, but the addition of six visible spectral bands together with one near infrared spectra provides a better background/foreground separation.

关键词： Tensile stress Matrix decomposition Streaming media Sparse matrices optimization Video surveillance Robustness

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Sliding Mode Control based Support Vector Machine RBF Kernel Parameter optimization

Sliding Mode Control based Support Vector Machine RBF Kernel...

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IEEE international workshop on Imaging Systems and Techniques (IST)

作者： Maryam Yalsavar Paknoosh Karimaghaee Akbar Sheikh-Akbari Jamshid Dehmeshki Mohammad-Hassan Khooban Salah Al-Majeed School of Electrical and Computer Engineering Shiraz University Shiraz Iran School of Built Environment Engineering and Computing Leeds Beckett University Leeds UK School School of Computer Science and Mathematics Kingston University London UK Applied Formal Methods Aarhus University Aarhus Denmark School of Business and Technology University of Gloucestershire Cheltenham UK

ISBN: (数字)9781728138688

ISBN: (纸本)9781728138695

Support Vector Machine (SVM) is a learning-based algorithm, which is widely used for classification in many applications. Despite its advantages, its application to large scale datasets is limited due to its use of large number of support vectors and dependency of its performance on its kernel parameter. This paper presents a Sliding Mode Control based Support Vector Machine Radial Basis Function's kernel parameter optimization (SMC-SVM-RBF) method, inspired by sliding mode closed loop control theory, which has demonstrated significantly higher performance to that of the standard closed loop control technique. The proposed method first defines an error equation and a sliding surface and then iteratively updates the RBF's kernel parameter based on the sliding mode control theory, forcing SVM training error to converge below a predefined threshold value. The closed loop nature of the proposed algorithm increases the robustness of the technique to uncertainty and improves its convergence speed. Experimental results were generated using nine standard benchmark datasets covering wide range of applications. Results show the proposed SMC-SVM-RBF method is significantly faster than those of classical SVM based techniques. Moreover, it generates more accurate results than most of the state of the art SVM based methods..

关键词： Support vector machines Kernel Training Sliding mode control Classification algorithms Training data Mathematical model

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