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Human action recognition based on multi-spatio-temporal features

Guangdianzi Jiguang/Journal of Optoelectronics Laser 2014年第10期25卷 2009-2017页

作者： Song, Jianming Zhang, Hua-Zhang Gao, Zan Zhang, Yan Xue, Yan-Bing Xu, Guang-Ping Key Laboratory of Computer Vision and System of Ministry of Education Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin China

Human action recognition is a hot research topic in video surveillance and human-computer interaction. In the past decades, human recognition algorithms based on single spatio-temporal feature have made great progress, and achieved good results. However, due to different spatio-temporal features have different characteristics and focus themselves, it is difficult for only one feature to completely describe human action. At the same time, when spatio-temporal interest points are projected into codebook, the codebook size is relatively large to achieve better performance, which hinders its practical application. Therefore, in order to solve the problem, human action recognition based on multi-spatio-temporal features is proposed, which can represent human action well and improve its reality. Large scale experiments on two public and challenging action recognition datasets-KTH and YouTube action datasets show that the proposed multi-spatio-temporal features using small size codebook have strong robustness, distinction and stability, whose performance is comparable to the state of the art algorithms.

关键词： Support vector machines

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Study of test classification algorithm based on domain knowledge

Study of test classification algorithm based on domain knowl...

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Third International Conference on Cyberspace technology (CCT 2015)

作者： Yutong Gao Feifan Song Xiaqing Xie Qing Sun Xu Wu Department of Computer Science and Information Engineering National Taipei University of Technology China School of Economics andManagement Beijing University of Posts and Telecommunications China Beijing University of Posts and Telecommunications Library China Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing China

When facing various and massive data resources, how to effectively utilize the resources according to the division field is one of the core problem of the institutional repository research. In this paper, we improved Bayesian classification algorithm, then proposed a text classification algorithm based on domain knowledge. Furthermore, some key technologies such as text classification, feature selection, weight improvement and domain knowledge algorithm improvement are designed and implemented. We use widely applied IkAnalyzer method to classify Chinese words. For feature selection and weight improvement part, we focus on the processing of special vocabulary in the document. We introduce the field expand vocabulary assist the Bayesian formula in the field application part to obtain the final result. The experiment result shows that the improved algorithm enhanced the accuracy of the classification efficiently, and the system calculating time is acceptable.

关键词： Bayesian Classification Domain Knowledge Institutional Repository Sorting Algorithms Text Classification domain knowledge Text categorization Sorting algorithm Feature extraction

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Solving economic dispatch problem in energy internet using a two-level stochastic gossip-based consensus algorithm

Solving economic dispatch problem in energy internet using a...

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2014 International Conference on Energy Research and Power Engineering, ERPE 2014

作者： Meng, Jie Zhang, Yan Zhang, Tao College of Information System and Management National University of Defense Technology Changsha China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha China

ISBN: (纸本)9783038351603

In the future, energy Internet will gradually replace the traditional power network since it enables flexible energy sharing for consumers. Consensus algorithm achieved good performance in solving economic dispatch problem in microgrid system whereas the difficulty is finding a consensus variable. By means of choosing the incremental generator cost of each energy local area network (ELAN) as the consensus variable, the economic dispatch problem can be solved. Using the stochastic gossip-based algorithm as the basic framework, the economic dispatch problem can be solved in a distributed manner. In order to meeting the real-time load requirement in time under the fixed communication topology, the fluctuation of each ELAN will do the consensus update at the same time. The result of a representative case is presented to illustrate the performance of the proposed two-level stochastic gossip-based consensus algorithm. © (2014) Trans Tech Publications, Switzerland.

关键词： Scheduling

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The roles of sampling zero dynamics in the discrete-time models for linear and nonlinear systems 33

The roles of sampling zero dynamics in the discrete-time mod...

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第三十三届中国控制会议

作者： LIANG Shan ZENG Cheng MITSUAKI Ishitobi ZHONG Jiaqi College of Automation Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Graduate School of Science and Technology Kumamoto University

ISBN: (纸本)9781479947249

It is well-known that the occurrence of sampling zero dynamics is relevant to the problem of discrete-time and sampled-data control for linear and nonlinear continuous-time *** particular,the sampling zero dynamics play also a very important role in the linear and nonlinear discrete-time transfer function and controller *** we explore some worthwhile results on the asymptotic properties of sampling zero dynamics to gain important new insights into the effect of sampling for linear and nonlinear *** results also demonstrate that the discrete-time models have to account,to some extent,for the sampling zero dynamics when considering the discrete dynamics behavior of the real control systems.

关键词： Sampling Zero Dynamics,Discrete-Time Models,Zero-Order Hold

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Online pedestrian tracking with kalman filter and random ferns

Online pedestrian tracking with kalman filter and random fer...

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2014 2nd International Conference on Mechatronics, Robotics and Automation, ICMRA 2014

作者： Qu, Zhi Qiang Tu, Dan Lei, Jun College of Information System and Management National University of Defense Technology ChangSha Hunan China State Key Laboratory of Mathmatical Engineering and Advanced Computing WuXi Jiangsu China

ISBN: (纸本)9783038350781

Object tracking is one of the most important components in numerous applications of computer vision. Much progress has been made in recent years. The Tracking-Learning-Detection (TLD) algorithm achieves excellent performance on a set of challenging video sequences. However, classical TLD algorithm fails to track non-rigid pedestrian as complicated appearance, varying viewpoints, shape changes and occlusions. In this paper, we follow the TLD and propose a robust KMD framework which consists of the Kalman filter tracker, random ferns pedestrian detector and the pedestrian model. During the tracking process the tracker and detector are complementary: the Kalman filter tracker predicts the motion, the pedestrian detector searches the best-match appearance and the pedestrian model combines performance of both to determine final result and generate new samples for learning. Experimental results show our framework comparatively improves performance for pedestrian tracking in surveillance videos. © (2014) Trans Tech Publications, Switzerland.

关键词： Kalman filters

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ADHD Discrimination Based on Social Network

ADHD Discrimination Based on Social Network

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International Conference on Cloud computing and Big Data (CCBD)

作者： Xiaojiao Guo Lianghua He The key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

ISBN: (纸本)9781479966226

Attention Deficit Hyperactivity Disorder (ADHD) is one of the common diseases of brain and has brought the growth of teenagers and even the adult indelible damage. It is very different to classify the ADHD symptoms and normal by the existing research. In this paper, the contributions are as two aspects: one is that the attributes of brain network of the resting state fMRI data have been calculated to discriminate three categories ADHD from the controls. And the average accuracies of various categories are 42.49% and 63.46% on the ADHD-200 datasets of NYU and KKI respectively, which is better than the average best imaging-based diagnostic performance of 35.19% and 61.90% achieved in the ADHD-200 global competition. The other one is that we put forward a new method named G-algorithm to construct the whole brain network, which based on certain rules. The same or even better classification results have been achieved by this method, which also verifies its feasibility and effectiveness.

关键词： Social network services Accuracy Support vector machines Correlation Synchronization Diseases Organizations

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MPC based approach for reliable power system energy management with high penetration level of renewable energy resources

MPC based approach for reliable power system energy manageme...

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2014 International Conference on Energy Research and Power Engineering, ERPE 2014

作者： Zhang, Yan Guo, Bo Zhang, Tao College of Information System and Management National University of Defense Technology Changsha 410073 China State Key Laboratory of High Performance Computing National University of Defense Technology Changsha 410073 China

ISBN: (纸本)9783038351603

This paper discusses using the battery energy storage system (BESS) to mitigate intermittency and sustain stability of distribution system integrating high penetration level of renewable energy resources (RER). The goal of the control is to have the BESS provide as much smoothing as possible, so that the RER power can be dispatchable in some kind and reliable. The effectiveness of model predictive control (MPC) based approach proposed in this paper have been tested by detail case study, also compared with the day ahead control strategy, load following strategy, and normal situation without energy storage which are usually used before. The result shows that the proposed MPC based approach is more practical, and more robust. © (2014) Trans Tech Publications, Switzerland.

关键词： Model predictive control

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A Method to Check Liveness of WS3PR 33

A Method to Check Liveness of WS3PR

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第三十三届中国控制会议

作者： WANG ShouGuang LIU Miao ZHOU MengChu WU WenHui IEEE School of Information & Electronic Engineering Zhejiang Gongshang University State Key Laboratory for Manufacturing Systems Engineering Xi’an Jiaotong University School of Electro-Mechanical Engineering Xidian University The Key Laboratory of Embedded System and Service Computing Ministry of EducationTongji University Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102USA

ISBN: (纸本)9781479947249

Petri nets are widely used to model flexible manufacturing systems(FMSs) because they can help analyze the properties and synthesize deadlock-free supervisory controllers of *** system of Simple Sequential Processes with Resources(WS3PR) is an important subclass of Petri nets that can well model many *** work first gives new algorithms to check liveness for a WS3 PR net via its subnet trees and *** the computation complexity for the proposed method is shown in this paper,to be polynomial under certain ***,sufficient conditions for deciding liveness of a WS3 PR are *** example is used to illustrate the results.

关键词： Liveness,flexible manufacturing system,deadlock,Petri net.

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Using estimation of distribution algorithm to coordinate decentralized learning automata for meta-task scheduling

Using estimation of distribution algorithm to coordinate dec...

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Congress on Evolutionary Computation

作者： Jie Li Junqi Zhang Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai China Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai Shanghai CN

Learning automaton (LA) is a reinforcement learning model that aims to determine the optimal action out of a set of actions. It is characterized by updating a selection probability vector through a sequence of repetitive feedback cycles interacting with an environment. Decentralized learning automata (DLAs) consists of many learning automata (LAs) that learn at the same time. Each LA independently selects an action based on its own selection probability vector. In order to provide an appropriate central coordination mechanism in DLAs, this paper proposes a novel decentralized coordination learning automaton (DCLA) using a new selection probability vector which is combined with the probability vectors derived from both LA and estimation of distribution algorithm (EDA). LA contributes to the own learning experience of each LA while EDA estimates the distribution of the whole swarm's promising individuals. Thus, decentralized LAs can be coordinated by EDA using the swarm's comprehensive knowledge. The proposed automaton is applied to solve the real problem of meta-task scheduling in heterogeneous computing system. Extensive experiments demonstrate a superiority of DCLA over other counterpart algorithms. The results show that the proposed DCLA provides an effective and efficient way to coordinate LAs for solving complicated problems.

关键词： Vectors Learning automata Sociology Statistics Processor scheduling Scheduling Estimation

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Adaptive multilevel meshes for cloth simulation

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Journal of Information and Computational Science 2014年第11期11卷 3865-3872页

作者： Zhao, Jing Pei, Shanshan Lv, Mengya Li, Ying Tang, Yong Yang, Meiling Zhang, Mingmin Pan, Zhigeng The College of Information Science and Engineering Yanshan University Qinhuangdao China The Key Laboratory for Computer Virtual Technology and System Integration of HeBei Province Qinhuangdao China The College of Computer Science and Technology Zhejiang University Hangzhou China Institute of Service Engineering Hangzhou Normal University Hangzhou China

A novel method based on multilevel meshes is proposed to simulate the cloth draping process rapidly on a complex model. Considering of the difficulty of computing the realtime collision between cloth and complex models by normally methods, the draping process of cloth is divided into several phases and at each phase the mesh size is smaller than its previous one. The optimized 1-to-4 split is used to drive the rapid changes in the grid hierarchy and to simplify the calculations. We choose the widely used ellipsoid as the bounding cell to enclose the complex models in the environment. The ellipsoid avoids the complex structure of hierarchical bounding box and eliminates the impossible collision model area rapidly. Experiments demonstrate that this method can accelerate the draping process of cloth and decrease the number of iterations and the calculation of collision detection. Further mesh refinement improves the reality of cloth when it reaches the final position and ensures the realism of the simulation in real time. ©2014 Binary Information Press

关键词： Mesh generation

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