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IEEE International Conference on Image Processing

作者： Xianyong Fang Feng Shen Yanwen Guo Christian Jacquemin Jian Zhou Shanchun Huang Anhui University Hefei Anhui CN Key Lab. of Intelligent Computing and Signal Processing Anhui University Hefei China State Key Lab. for Novel Software Technology Nanjing University Nanjing China AMI LIMSI-CNRS Orsay France

Despite numerous efforts on blur measurement of partially blurred images, there still lacks an effective blur measure that is both pixel-wise and locally sharp consistent. The paper proposes a novel method with two contributions to overcome this limitation: 1) A new pixel-based blur metric, Multi-resolution Singular Value (MSV), which leverages the average singular value of high frequency bands to measure the blur of each pixel, and 2) a locally continuous strategy, maximum-likelihood estimation (MLE) based refinement, that ensures local continuity by imposing the local sharp consistency on pixel blur in a local correcting process. Experimental results show that our method is effective to smoothly measure the partially blurred images without local discontinuity.

关键词： Maximum likelihood estimation Equations Frequency measurement Image edge detection Mathematical model Wavelet transforms

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BLOCKY ARTIFACT REMOVAL WITH LOW-RANK MATRIX RECOVERY

BLOCKY ARTIFACT REMOVAL WITH LOW-RANK MATRIX RECOVERY

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Ming Yin Junbin Gao Yanfeng Sun Shuting Cai School of Automation Guangdong University of Technology Guangzhou 510006 China School of Computing and Mathematics Charles Sturt University Bathurst NSW 2795 Australia Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology Beijing University of Technology Beijing 100124 China

ISBN: (纸本)9781479928941

In this paper, a novel image blocky artifact removal scheme based on low-rank matrix recovery is proposed. The problem of suppressing blocky artifacts is formulated as recovering a low-rank matrix from corrupted observations. During the deblocking processing, we do not directly recover the whole clean image but only its high-frequency component and then synthesize the clean image by incorporating the low-frequency component of blocky image. To take advantage of the low-rank matrix recovery paradigm, we first cluster the similar patches of the high-frequency component of image via local pixel clustering, then the clean high-frequency component of image is recovered by formulating an optimization problem of the nuclear norm and l_1-norm. The experimental results show that the proposed algorithm can achieve competitive performance in terms of both quantitative and subjective quality.

关键词： Imagery (Psychotherapy) images Image High frequency rank of matrix Artifacts matrix matrices

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Dimensionality Reduction Assisted Tensor Clustering

Dimensionality Reduction Assisted Tensor Clustering

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International Joint Conference on Neural Networks

作者： Yanfeng Sun Junbin Gao Xia Hong Yi Guo Chris J. Harris Beijing Municipal Key Lab of Multimedia and Intelligent Software Technology Beijing University of Technology School of Computing and Mathematics Charles Sturt University School of Systems Engineering University of Reading CSIRO Mathematics Informatics and Statistics Electronics and Computer Science University of Southampton

ISBN: (纸本)9781479914821

This paper is concerned with tensor clustering with the assistance of dimensionality reduction approaches. A class of formulation for tensor clustering is introduced based on tensor Tucker decomposition models. In this formulation, an extra tensor mode is formed by a collection of tensors of the same dimensions and then used to assist a Tucker decomposition in order to achieve data dimensionality reduction. We design two types of clustering models for the tensors: PCA Tensor Clustering model and Non-negative Tensor Clustering model, by utilizing different regularizations. The tensor clustering can thus be solved by the optimization method based on the alternative coordinate scheme. Interestingly, our experiments show that the proposed models yield comparable or even better performance compared to most recent clustering algorithms based on matrix factorization.

关键词： Tensor Tucker Decomposition Tensor Clustering Matrix Factorization Tensor PCA

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A mobile phone palmprint verification system using gabor-based sdlpp

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ICIC Express Letters, Part B: Applications 2014年第6期5卷 1667-1672页

作者： Zhang, Jianxin Zhang, Zhange Ou, Zongying Zhang, Qiang Key Lab of Advanced Design and Intelligent Computing Ministry of Education Dalian University No. 10 Xuefu Street Jinzhou New District Dalian China Materials and Energy Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian China

The paper presents a mobile phone palmprint verification system based on novel image capture and feature extraction approaches. The system captures part regions of palm with four fingers closing together and parallel to screen. Then ROI image can be located by detecting key points of fingers region. For feature extraction step, optimal Gabor features of different scales and orientations are extracted from ROI images, and then SDLPP is applied for the dimensionality reduction of Gabor feature space to provide a more compact and discriminant representation. The system achieves the verification accuracy of EER = 3.43% and takes less than 1s to verify a palmprint image, which can satisfy the requirement of a real-time verification system.

关键词： Cellular telephones

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26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 Antwerp, Belgium. 15-20 July 2017 Abstracts

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BMC NEUROSCIENCE 2017年第SUPPL 1期18卷 95-176页

作者： [Anonymous] Department of Neuroscience Yale University New Haven CT 06520 USA Department Physiology & Pharmacology SUNY Downstate Brooklyn NY 11203 USA NYU School of Engineering 6 MetroTech Center Brooklyn NY 11201 USA Departament de Matemàtica Aplicada Universitat Politècnica de Catalunya Barcelona 08028 Spain Institut de Neurobiologie de la Méditerrannée (INMED) INSERM UMR901 Aix-Marseille Univ Marseille France Center of Neural Science New York University New York NY USA Aix-Marseille Univ INSERM INS Inst Neurosci Syst Marseille France Laboratoire de Physique Théorique et Modélisation CNRS UMR 8089 Université de Cergy-Pontoise 95300 Cergy-Pontoise Cedex France Department of Mathematics and Computer Science ENSAT Abdelmalek Essaadi’s University Tangier Morocco Laboratory of Natural Computation Department of Information and Electrical Engineering and Applied Mathematics University of Salerno 84084 Fisciano SA Italy Department of Medicine University of Salerno 84083 Lancusi SA Italy Dipartimento di Fisica Università degli Studi Aldo Moro Bari and INFN Sezione Di Bari Italy Data Analysis Department Ghent University Ghent Belgium Coma Science Group University of Liège Liège Belgium Cruces Hospital and Ikerbasque Research Center Bilbao Spain BIOtech Department of Industrial Engineering University of Trento and IRCS-PAT FBK 38010 Trento Italy Department of Data Analysis Ghent University Ghent 9000 Belgium The Wellcome Trust Centre for Neuroimaging University College London London WC1N 3BG UK Department of Electronic Engineering NED University of Engineering and Technology Karachi Pakistan Blue Brain Project École Polytechnique Fédérale de Lausanne Lausanne Switzerland Departement of Mathematics Swansea University Swansea Wales UK Laboratory for Topology and Neuroscience at the Brain Mind Institute École polytechnique fédérale de Lausanne Lausanne Switzerland Institute of Mathematics University of Aberdeen Aberdeen Scotland UK Department of Integrativ

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Study on the application of virtual reality technology in the production of industrial products based on OpenGL

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5th International Conference on Mechanical and Electrical technology, ICMET 2013

作者： Wang, Fa Yu Wang, Jing Chao Lu, Baoan Ministry of Education Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China

ISBN: (纸本)9783037858349

This paper mainly discusses the use of virtual reality technology to make the complex steel production environment into direct, simple virtual interface. The model of square steel and the model of cylindrical steel have been founded through object-oriented method and powerful 3D image edit function provided by OpenGL which is employed in this system. Simulation system framework and friendly man-machine interaction are founded using 3-tier application for interactive control. The establishment and maintenance of the steel template, the real-time processing of the temperature in the steel production. © (2013) Trans Tech Publications, Switzerland.

关键词： Human computer interaction

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Design of robot lawn mower based on computer vision

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2nd International Symposium on Manufacturing Systems Engineering, ISMSE 2013

作者： Wang, Fa Yu Gao, Zhen Li Yin, Hong Yu Ministry of Education Tianjin University of Technology Tianjin 300384 China Tianjin Key Lab of Intelligent Computing and Novel Software Technology Tianjin University of Technology Tianjin 300384 China

ISBN: (纸本)9783037858455

In this paper, we introduce a new research about mowing robot on obstacle avoidance and path tracking controlling theoretically and practically, and propose the mowing control method which based on computer vision. Lawn images collected by camera, through the extraction of programming dealing with lawn, obstacles and boundary characteristics to achieve edge separation. Through special processing algorithm to determine boundary arises and obstacles location, size and speed of the robot, with real-time capturing and processing. This paper gives the complete image recognition processing, and analyzes several methods of image filtering and edge detection, and proposes simple control algorithm for obstacle avoidance, and applies MATlab for obstacle avoidance simulation. The results show that: the method can correctly identify the obstacles and boundaries, through the output about location, size of the obstacles and boundary, border slope and speed of the robot to control robot mower. Most importantly, that computer vision applying in the mowing robot itself is an innovation. © (2013) Trans Tech Publications, Switzerland.

关键词： Computer vision

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Flexible navigation in smartphones and tablets using scalable storyboards 13

Flexible navigation in smartphones and tablets using scalabl...

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3rd ACM International Conference on Multimedia Retrieval, ICMR 2013

作者： Zheng, Shuai Herranz, Luis Jiang, Shuqiang Key Lab. of Intelligent Information Processing Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China School of Software Engineering Beijing Jiaotong University Beijing 100044 China

ISBN: (纸本)9781450320337

In this demo paper we present a multiscale browsing interface for handheld devices, in which the user can interactively change the scale of the storyboard to easily adjust the amount of information desired. Conventional and hierarchical storyboards provide one or very few possible lengths. In contrast, scalable storyboards allow the number of images and the storyboard itself to be adapted to the device constraints (e.g. aspect ratio, resolution) and navigation state with much finer granularity. Several levels and modes, including segment of interest, are provided for more intuitive and convenient navigation. © 2013 Authors.

关键词： Aspect ratio

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Endmember extraction by exemplar finder

Endmember extraction by exemplar finder

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9th International Conference on Advanced Data Mining and Applications, ADMA 2013

作者： Guo, Yi Gao, Junbin Sun, Yanfeng CSIRO Division of Computational Informatics North Ryde NSW 1670 Australia School of Computing and Mathematics Charles Sturt University Bathurst NSW 2795 Australia Beijing Municipal Key Lab. of Multimedia and Intelligent Software Technology Beijing University of Technology Beijing 100124 China

ISBN: (纸本)9783642539169

We propose a novel method called exemplar finder (EF) for spectral data endmember extraction problem, which is also known as blind unmixing in remote sensing community. Exemplar finder is based on data self reconstruction assuming that the bases (endmembers) generating the data exist in the given data set. The bases selection is fulfilled by minimising a l2/l1 norm on the reconstruction coefficients, which eliminates or suppresses irrelevant weights from non-exemplar samples. As a result, it is able to identify endmembers automatically. This algorithm can be further extended, for example, using different error structures and including rank operator. We test this method on semi-simulated hyperspectral data where ground truth is available. Exemplar finder successfully identifies endmembers, which is far better than some existing methods, especially when signal to noise ratio is high. © 2013 Springer-Verlag.

关键词： Signal to noise ratio

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