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Video processing techniques for traffic flow monitoring: A survey

Video processing techniques for traffic flow monitoring: A s...

引用

International Conference on intelligent Transportation

作者： Bin Tian Qingming Yao Yuan Gu Kunfeng Wang Ye Li State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China Jiangsu China Sciences Intelligent Engineering Co. Ltd. Suzhou 215000 China Institute of Automation Chinese Academy of Sciences (CAS) Beijing China State Key Laboratory of Intelligent Control and Management Institute of Automation Chinese Academy of Sciences (CAS) Beijing China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

Video-based traffic flow monitoring is a fast emerging field based on the continuous development of computer vision. A survey of the state-of-the-art video processing techniques in traffic flow monitoring is presented in this paper. Firstly, vehicle detection is the first step of video processing and detection methods are classified into background modeling based methods and non-background modeling based methods. In particular, nighttime detection is more challenging due to bad illumination and sensitivity to light. Then tracking techniques, including 3D model-based, region-based, active contour-based and feature-based tracking, are presented. A variety of algorithms including MeanShift algorithm, Kalman Filter and Particle Filter are applied in tracking process. In addition, shadow detection and vehicles occlusion bring much trouble into vehicle detection, tracking and so on. Based on the aforementioned video processing techniques, discussion on behavior understanding including traffic incident detection is carried out. Finally, key challenges in traffic flow monitoring are discussed.

关键词： Vehicles Monitoring Tracking Vehicle detection Image edge detection Trajectory Computational modeling

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Polarity Shifting: Corpus Construction and Analysis

Polarity Shifting: Corpus Construction and Analysis

引用

International Conference on Asian Language Processing (IALP)

作者： Xiaoqian Zhang Shoushan Li Guodong Zhou Hongxia Zhao Natural Language Processing Laboratory Soochow University Suzhou China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Polarity shifting has been a challenge to automatic sentiment classification. In this paper, we create a corpus which consists of polarity-shifted sentences in various kinds of product reviews. In the corpus, both the sentimental words and shifting trigger words are annotated. Furthermore, we analyze all the polarity shifted sentences and categorize them into five categories: opinion-itself, holder, target, time and hypothesis. Experimental study shows the agreement of annotation and the distribution of the five categories of polarity shifting.

关键词： Machine learning Dictionaries Computational linguistics Manuals Noise Data mining Vectors

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Vulnerability analysis of power grid based on multi-agent complex systems

Vulnerability analysis of power grid based on multi-agent co...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xisong Dong Gang Xiong Jiachen Hou Fan Dong Timo R. Nyberg State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China BIT Research Centre Aalto University Aalto Finland

Modern power grid is a typical multi-level complex giant system. The conventional analytical methods based on reductionism can't provide sufficient guidance for its operation and management. complex system theory, based on holism, has its specific advantages in power grid's research. But, it has some limitations. In this article, we improve complex grid by introducing new parameters which can describe the grid's characters better and using multi-agent theory. As an application, the complex power grid constructed with actual data from North China grid is constructed and its vulnerability has been simulated and analyzed under different attacks.

关键词： Knowledge engineering Databases

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Video vehicle detection through multiple background-based features and statistical learning

Video vehicle detection through multiple background-based fe...

引用

International Conference on intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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Mobile robot's electronic compass calibration based on modified Fourier Neural Network

Mobile robot's electronic compass calibration based on modif...

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IEEE Conference on Robotics, automation and Mechatronics

作者： Gong Kun Deng Fang Ma Tao Gong Kun is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Deng Fang is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Ma Tao is with School of Automation Beijing Institute of Technology and Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

In order to improve the precision of the azimuth measured by mobile robot's electronic compass, this paper proposes a new calibration method based on Fourier Neural Network trained by Modified Particle Swarm Optimization (MPSO-FNN). This method makes use of Fourier Neural Network (FNN) to establish the error compensation model of electronic compass's azimuth, and introduces Modified Particle Swarm Optimization (MPSO) algorithm to optimize the weights of neural network. Thus the comparatively accurate error model of azimuth is obtained to compensate the output of electronic compass. This method not only has strong nonlinear approximation capability, but also overcomes the neural networks' shortcomings which are too slow convergence speed, oscillation, and easy to fall into local optimum and sensitive to the initial values. Experimental results demonstrate that after calibrated by this method, the range of azimuth error reduces to -0.35°~0.70° from -3.4°~25.2°, and the average value of absolute error is only 0.30°.

关键词： Compass Azimuth Biological neural networks Particle swarm optimization Training Accuracy automation

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Fast double-parallel image processing based on FPGA

Fast double-parallel image processing based on FPGA

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IEEE International Conference on Vehicular Electronics and Safety (ICVES)

作者： Ye Li Qingming Yao Bin Tian Wencong Xu State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy and Sciences Beijing China School of Mechanical Electrical and Information Engineering Shandong University Weihai China

Due to FPGA's flexibility and parallelism, it is popular for accelerating image processing. In this paper, a double-parallel architecture based on FPGA has been exploited to speed up median filter and edge detection tasks, which are essential steps during image processing. The double-parallel scheme includes an image-level parallel and an operation-level parallel. The image-level parallel is a high-level parallel which divides one image into different parts and processes them concurrently. The operation-level parallel, which is embedded in each image-level parallel thread, fully explores every parallel part inside the concrete algorithms. The corresponding design is based on a DE2 Development Board which contains a CYCLONE II FPGA device. Meanwhile, the same task has also been implemented on PC and DSP for performance comparison. Despite the fact that operating frequencies of used PC and DSP are much higher than FPGA's, FPGA costs less time per computed image than both of them. By taking advantage of the double-parallel technique, the speed/frequency ratio of FPGA is 202 times faster than PC and 147 times faster than DSP. Finally, a detailed discussion about different platforms is conducted, which analyzes advantages and disadvantages of used computing platforms. This paper reveals that the proposed double-parallel scheme can dramatically speed up image processing methods even on a low-cost FPGA platform with low frequency and limited resources, which is very meaningful for practical applications.

关键词： Image edge detection Field programmable gate arrays Digital signal processing Hardware Kernel Detectors

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Improved differential evolution-based particle filter algorithm for target tracking

Improved differential evolution-based particle filter algori...

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作者： Wang, Yanan Chen, Jie Gan, Minggang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education BIT Beijing 100081 China

ISBN: (纸本)9789881725592

This paper presents an improved target tracking algorithm based on the differential evolution particle filter (DEPF) in order to solve the problem of particle degeneracy. In this method, the mutation, crossover and selection steps of the differential evolution are introduced into the particle filter, which optimizes the particle sampling process. Particles are moved towards regions where they are close to the value of the posterior density function through DEPF algorithm, and it improves the estimation precision, inhibits the particle degeneracy and enhances the diversity of the particles. The target observation model based on the color feature is constructed simultaneously in the algorithm, and the method of the target model update in different states is also studied. The experimental results show that the target even in attitude change and occlusion can be tracked accurately and real-timely with the DEPF algorithm. The proposed algorithm has higher tracking accuracy and is robust. © 2011 Chinese Assoc of automation.

关键词： Target tracking

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Impulsive control method based on improved differential evolution algorithm

Impulsive control method based on improved differential evol...

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作者： Zhao, Juan Cai, Tao Deng, Fang Yang, Hongwei School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education BIT Beijing 100081 China

ISBN: (纸本)9789881725592

In this paper, a new strategy based on impulsive control model of high speed roller is proposed. To make the roller hit the specified target, the strategy is summarized as an optimal control model calculating required number of impulses, the igniting time and phase of each impulse, and also an improved Differential Evolution (DE) Algorithm is adopted to resolve. It is too difficult to solve the orderliness of igniting time by Basic DE, so a Mapping Differential Evolution Algorithm (MDE) is proposed, which maps the sorting time variables to random coefficient range [0,1]. In addition, a DE with self-adapting parameter is used to accelerate the convergence rate. Simulation results show the high accuracy of high speed roller with the method. © 2011 Chinese Assoc of Automati.

关键词： Mapping

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Agent-based traffic simulation and traffic signal timing optimization with GPU

Agent-based traffic simulation and traffic signal timing opt...

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International Conference on intelligent Transportation

作者： Zhen Shen Kai Wang Fenghua Zhu State Key Laboratory of Intelligent Control and Management of Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences (CAS) Beijing China Center of Military Computational Experiments and Parallel Systems Technology and College of Mechatronics Engineering and Automation National University of Defense Technology Changsha Hunan China

With the advantage of simulating the details of a transportation system, the “microsimulation” of a traffic system has long been a hot topic in the intelligent Transportation systems (ITS) research. The Cellular Automata (CA) and the Multi-Agent System (MAS) modeling are two typical methods for the traffic microsimulation. However, the computing burden for the microsimulation and the optimization based on it is usually very heavy. In recent years the Graphics Processing Units (GPUs) have been applied successfully in many areas for parallel computing. Compared with the traditional CPU cluster, GPU has an obvious advantage of low cost of hardware and electricity consumption. In this paper we build an MAS model for a road network of four signalized intersections and we use a Genetic Algorithm (GA) to optimize the traffic signal timing with the objective of maximizing the number of the vehicles leaving the network in a given period of time. Both the simulation and the optimization are accelerated by GPU and a speedup by a factor of 195 is obtained. In the future we will extend the work to large scale road networks.

关键词： Graphics processing unit Vehicles Roads Optimization Computational modeling Genetic algorithms Timing

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An optimized modeling method based on BPEL4WS

An optimized modeling method based on BPEL4WS

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Sheng Liu Gang Xiong Dong Fan Jianshi Yao State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Science Beijing 100190 China Unit 61541 The Chinese People's Liberation Army Beijing 100094 China

As an efficient business process execution language which supports web services, BPEL4WS is widely supported by the academic and the industrial circles. According to the shortcomings such as number of computer terms, abstract model definition and the complex description of people activity, this paper presents easy-to-use BPEL4WS modeling method and tool which encapsulates computer terms and convert business models to BPEL4WS models directly. In comparison to the other modeling methods, our method cut down the number of modeling elements by more than 85 percent and save the modeling time by 80 percent and accelerate model running by more than 40 percent. Thus it is more appropriate for popularization.

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