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Data Compression Conference (DCC)

作者： Deming Zhai Xianming Liu Debin Zhao Hong Chang Wen Gao School of Computer Science and Technology Harbin Institute of Technology Harbin China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Harbin Institute of Technology Harbin Heilongjiang CN

ISBN: (纸本)9781467360371

In this paper, we propose a unified framework to perform progressive image restoration based on hybrid graph Laplacian regularized regression. We first construct a multi-scale representation of the target image by Laplacian pyramid, then progressively recover the degraded image in the scale space from coarse to fine so that the sharp edges and texture can be eventually recovered. On one hand, within each scale, a graph Laplacian regularization model represented by implicit kernel is learned which simultaneously minimizes the least square error on the measured samples and preserves the geometrical structure of the image data space by exploring non-local self-similarity. In this procedure, the intrinsic manifold structure is considered by using both measured and unmeasured samples. On the other hand, between two scales, the proposed model is extended to the parametric manner through explicit kernel mapping to model the inter-scale correlation, in which the local structure regularity is learned and propagated from coarser to finer scales. Experimental results on benchmark test images demonstrate that the proposed method achieves better performance than state-of-the-art image restoration algorithms.

关键词： Kernel Noise Image restoration Laplace equations Noise measurement Manifolds Linear programming

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Robust and accurate moving shadow detection based on multiple features fusion

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Optics & Laser technology 2013年 54卷 232-241页

作者： Jiangyan Dai Miao Qi Jianzhong Wang Jiangkun Dai Jun Kong School of Computer Science and Information Technology Northeast Normal University Key Laboratory of Intelligent Information Processing of Jilin Universities Changchun China School of Mathematics and Statistics Northeast Normal University Changchun China College of Science Northwest A&F University Yangling Shanxi China

In recent years, moving cast shadow detection has been becoming a critical challenge to improve the accuracy of moving object detection in video surveillance. In this paper, we derive a robust moving cast shadow detection method based on multiple features fusion. Firstly, several kinds of features such as intensity, color and texture are extracted sufficiently by means of various measures for the foreground image. Then, the synthetic feature map is generated by linear combination of these features. Consequently, moving cast shadow pixels are distinguished from their moving objects roughly. Finally, spatial adjustment is applied to correct misclassified pixels for acquiring the refined shadow detection result. The effectiveness of our proposed method is evaluated on various scenes. The results demonstrate that the method can achieve high detection rate. In particular, the experiments also indicate that it significantly outperforms several state-of-the-art methods by extensive comparisons.

关键词： Shadow detection Object segmentation Feature fusion

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Mining top-K Frequent and Flexible Pattern from sequences

Mining top-K Frequent and Flexible Pattern from sequences

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IEEE Conference Anthology

作者： Zhang Junyan Min Fan University Key Laboratory of Pattern Recognition and Intelligent information Processing Chengdu Sichuan Province China School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China

Pattern Mining is a popular issue in biological sequence analysis. With the introduction of wildcard gaps, more interesting patterns can be mined. In this paper, we propose a new definition related to pattern frequency, under which the Apriori property holds. We define a pattern mining problem called Ming top-K Frequent Patterns (MFP), where gaps are mined instead of specified. Compared with existing problems, MFP does not require any domain knowledge of the user. However, theoretical analysis and experimental results show that MFP favors inflexible patterns. We then define another problem where the flexibility threshold of each gap is specified by the user. The problem is called Mining top-K Frequent and Flexible Patterns (MF 2 P). We develop algorithm with polynomial complexities for both problems. Patterns can grow from both sides. Some interesting biological patterns mined by our algorithms are discussed.

关键词： constraints pattern mining sequence wildcard gap

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Small Universal Sequential Spiking Neural P Systems based on Minimum Spike Number

Small Universal Sequential Spiking Neural P Systems based on...

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The Second Asian Conference on Membrane Computing(ACMC2013)

作者： Keqin Jiang Yufang Huang Jinbang Xu Zhihua Chen Key Laboratory of Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology School of Computer and Information Anqing Normal University College of Mathematics Southwest Jiaotong University

Spiking neural P systems (SN P systems, for short) are a class of distributed parallel computing devices inspired from the way neurons communicate by means of spikes. Recently, a variant of SN P systems was considered: at each step the neuron with the minimum number of spikes among the neurons that can spike will fire. In previous literature, it was obtained that such systems can achieve Turing completeness when the computing result is realized through accumulation of spikes in the output neuron. In this work, we use a natural way to define the computing result of the systems, by means of determining the time interval between the first two spikes emitted by the output neuron. As devices of computing functions, we construct a universal sequential SN P system based on minimum spike number (without delay) by using 137 neurons;as generators of sets of numbers, a universal sequential SN P system based on minimum spike number (without delay) with 126 neurons is also obtained.

关键词： Membrane computing, Spiking neural P system, Sequentiality, Small universal system

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Distributed Leader-following Swarm of Heterogeneous Multi-agent Systems *

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IFAC Proceedings Volumes 2013年第13期46卷 13-18页

作者： Haili Liang Housheng Su Xiaofan Wang Michael Z.Q. Chen Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China Department of Mechanical Engineering The University of Hong Kong Hong Kong

This paper investigates distributed leader-following swarm of heterogeneous multi-agent systems. Comparing with the existing works on leader-following swarm of homogeneous multi-agent systems, this paper is much more approaching the practical situation because the agents have different dynamics. We show that the heterogeneous followers will gather with a certain error lever under some assumptions and conditions. The stability properties have been proven by theoretical analysis and verified via numerical simulation. The stability of the heterogeneous multi-agent systems has been achieved based on matrix theory and the Lyapunov stability theorem. Numerical simulation is given to demonstrate the effectiveness of the theoretical result.

关键词： Swarm Multi-agent systems Heterogeneous systems Distributed control

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Swarm Stability of Heterogeneous Multi-agent Systems via Periodically Intermittent Control

Swarm Stability of Heterogeneous Multi-agent Systems via Per...

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第三十二届中国控制会议

作者： Haili Liang Housheng Su Xiaofan Wang Michael Z. Q. Chen Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Department of Mechanical Engineering The University of Hong Kong

ISBN: (纸本)9789881563835

This paper investigates distributed leader-following swarm stability of heterogeneous multi-agent systems with periodically intermittent control. We assume that the agents in the network are nonidentical and the coupling matrix is balanced. Each heterogeneous follower is assumed to obtain some information from the leader and the neighbors only on a series of periodically time intervals. We show that the system will be exponentially stable. The stability properties are proved via theoretical analysis and verified via numerical simulations. The stability of the heterogeneous multi-agent systems is proved based on matrix theory and the Lyapunov stability theorem. A numerical example is shown to demonstrate the effectiveness of the theoretical result.

关键词： Multi-agent systems, Heterogeneous systems, Intermittent control, Swarm

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Synchronic Analysis in a Neural Network Based on FitzHugh-Nagumo Equations with Time Delay

Synchronic Analysis in a Neural Network Based on FitzHugh-Na...

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2013 ICME International Conference on Complex Medical Engineering(2013 ICME复合医学工程国际会议)

作者： Shurui Qin Yuanhua Qiao Jun Miao Lijuan Duan College of Applied Science Beijing University of Technology Beijing 100124 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acad College of Computer Science Beijing University of Technology Beijing 100124 China

The dynamics of a neuronal network often involves time delay due to the finite signal propagation speed in biological *** this paper,we make some analysis on the FitzHugh-Nagumo model with coupling delay and then inve... 详细信息

ISBN: (纸本)9781467329705

关键词： FitzHugh-Nagumo model neural network synchronization time delay

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TriggerCas: Enabling wireless consrucive collisions

TriggerCas: Enabling wireless consrucive collisions

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Yin Wang Yuan He Dapeng Cheng Yunhao Liu Xiang-yang Li MOE Key Laboratory for Information System Security School of Software TNLIST Tsinghua University China Department of Computer Science and Engineering Hong Kong University of Science and Technology Hong Kong China Key Laboratory of Intelligent Information Processing Universities of Shandong China Department of Computer Science Illinois Institute of Technology USA

Constructive Interference (CI) proposed in the existing work (e.g., A-MAC [1], Glossy [2]) may degrade the packet reception performance in terms of Packet Reception Ratio (PRR) and Received Signal Strength Indication (RSSI). The packet reception performance of a set of nodes transmitting simultaneously might be no better than that of any single node transmitting individually. In this paper, we redefine CI and propose TriggerCast, a practical wireless architecture which ensures concurrent transmissions of an identical packet to interfere constructively rather than to interfere non-destructively. CI potentially allows orders of magnitude reductions in energy consumption and improvements in link quality. Moreover, we for the first time present a theoretical sufficient condition for generating CI with IEEE 802.15.4 radio: concurrent transmissions with an identical packet should be synchronized at chip level. Meanwhile, co-senders participating in concurrent transmissions should be carefully selected, and the starting instants for the concurrent transmissions should be aligned. Based on the sufficient condition, we propose practical techniques to effectively compensate propagation and radio processing delays. TriggerCast has 95 th percentile synchronization errors of at most 250ns. Extensive experiments in practical testbeds reveal that TriggerCast significantly improves PRR (from 5% to 70% with 7 concurrent senders, from 50% to 98.3% with 6 senders) and RSSI (about 6dB with 5 senders).

关键词： Delays Synchronization Signal to noise ratio Receivers Wireless sensor networks IEEE 802.15 Standards

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Variable structure multiple model for articulated human motion tracking from monocular video sequences

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Science China(information Sciences) 2012年第5期55卷 1138-1150页

作者： HAN Hong 1,TONG MingLei 2,CHEN ZhiChao 1 & FAN YouJian 1 1 key laboratory of intelligent perception and Image Understanding of Ministry of Education of China,Institute of intelligent information processing,Xidian University,Xi'an 710071,China 2 School of Computer and information Engineering,Shanghai University of Electric Power,Shanghai 200090,China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an China School of Computer and Information Engineering Shanghai University of Electric Power Shanghai China

A new model-based human body tracking framework with learning-based theory is introduced in this *** propose a variable structure multiple model (VSMM) framework to address challenging problems such as uncertainty of motion styles,imprecise detection of feature points,and ambiguity of joint *** human joint points are detected automatically and the undetected points are estimated with Kalman *** motion models are learned from motion capture data using a ridge regression *** model set that covers the total motion set is designed on the basis of topological and compatibility relationships,while the VSMM algorithm is used to estimate quaternion vectors of joint *** using real image sequences and simulation videos demonstrate the high efficiency of our proposed human tracking framework.

关键词： human motion tracking ridge regression model groups design variable structure multiple model (VSMM) motion model group adaptation

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Moving vehicle detection and tracking in traffic images based on horizontal edges

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Telkomnika - Indonesian Journal of Electrical Engineering 2013年第11期11卷 6477-6483页

作者： Zhu, Hongjin Fan, Honghui Guo, Shuqiang School of Computer Engineering Jiangsu University of Technology Changzhou 213001 Jiangsu China Key Laboratory of Cloud Computing Intelligent Information Processing of Changzhou City China School of Information Engineering Northeast Dianli University Jilin 132012 Jilin China

This paper presents a moving vehicle detection and tracking system, which comprising of Horizontal Edges method and Local Auto Correlation. Horizontal Edges characteristic can be strengthened and the influence of weather condition is reduced by using Local Auto Correlation, so the detection rate of extracting and tracking moving vehicles with horizontal edge can be raised. Local Auto Correlation images are generated for vehicle detection and based on Horizontal Edges method. The distance of the gravity center of Horizontal Edges is used to track vehicles in traffic video. We verify the system using a variety of weather (in fog, car shadow existence, morning and evening) traffic video. Experimental results have shown that the high detection rate of moving vehicles be obtained by using the proposed method. © 2013 Universitas Ahmad Dahlan.

关键词： Tracking (position)

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