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Graph-Based Background Suppression for Scene Text Detection

Graph-Based Background Suppression for Scene Text Detection

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IAPR International Workshop on Document Analysis systems, DAS

作者： Cunzhao Shi Baihua Xiao Chunheng Wang Yang Zhang State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Detecting text in video or natural scene image is quite challenging due to the complex background, various fonts and illumination conditions. The preprocessing period, which suppresses the nontext areas so as to highlight the text areas, is the basis for further text detection. In this paper, a novel graph-based background suppression method for scene text detection is proposed. Considering each pixel as a node in the graph, our approach incorporates pixel-level and context-level features into a graph. Various factors contribute to the unary and pair wise cost function which is optimized via max-flow/min-cut algorithm [16] to get a binary image whose nontext pixels are suppressed so that text pixels are highlighted. Furthermore, the proposed background suppression method could be easily combined with other detection methods to improve the performance. Experimental results on ICDAR 2011 competition dataset show promising performance.

关键词： Image edge detection Cost function Image color analysis Text categorization Feature extraction Computer vision

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A new discrete-time guidance law base on trajectory learning and prediction

A new discrete-time guidance law base on trajectory learning...

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AIAA Guidance, Navigation, and control Conference 2012

作者： Ma, Hong Bin Wang, Ming Zhe Fu, Meng Yin Yang, Chen Guang Beijing Institute of Technology Beijing China University of Plymouth Plymouth United Kingdom Key Laboratory of Intelligent Control Decision of Complex Systems Beijing 100081 China School of Computing and Mathematics Plymouth PL4 8AA United Kingdom

ISBN: (数字)9781600869389

ISBN: (纸本)9781600869389

A new data-driven predictive discrete-time guidance law is presented for an interceptor pursuing a target which can perform arbitrary maneuver. The designed guidance law is driven by observed data of certain steps, which record previous positions of the target and make it feasible to estimate the behavior of the target and hence design the guidance command at each step by solving an time-dependent optimization problem, and this feature distinguishes the proposed guidance law from those traditional guidance laws which are usually described by an ordinary differential equations and use only the measurement at current time instant. To verify the performance of the new guidance law proposed, extensive simulations were carried out to compare it with some typical existing guidance laws like pursuit guidance (PG), beamer rider (BR) guidance, constant bearing (CB) guidance and proportional navigation (PN) law. The simulation studies show that the new predictive guidance law (abbreviated as LP) can provide comparative performance in all the cases studied, and it can even outperform other guidance laws when the target performs random maneuver, which show that the proposed guidance scheme exhibits certain robustness and adaptation. © 2012 by Hongbin Ma, on behalf of Beijing Institute of Technology.

关键词： Ordinary differential equations

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GPU based ordinal optimization for traffic signal coordination

GPU based ordinal optimization for traffic signal coordinati...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Wang, Kai Shen, Zhen Changsha Hunan China State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Center Chinese Academy of Sciences Songshan Lake Dongguan 523808 Guangdong Province China

ISBN: (纸本)9781467324007

Traffic signal coordination has long been a hot topic in intelligent Transportation systems (ITS) research. Simulation-based optimization is an important method to optimize the coordination designs as the traffic systems are not easily described by mathematical models accurately. For the traffic simulator in the method, micro-simulation is becoming more and more popular than the macroscopic or mesoscopic simulation in recent years, as the micro-simulation can describe drivers' decision-making process and their driving behaviors in the framework of ITS. However, the computing burden for the micro-simulation is usually very heavy as a large number of vehicles are modeled and simulated separately. For the optimizer in the method, iterative algorithms such as Genetic Algorithms (GA), Ant Colony optimization (ACO), and Particle Swarm optimization (PSO) are widely used to find the global optimal solutions. However, these algorithms usually take too much time to converge when a large-scale road network is encountered. To alleviate the computing burden and speed up the convergence, we build an agent-based traffic simulator and employ Ordinal optimization (OO) as the optimizer. We accelerate both the simulator and the optimizer with Graphics Processing Unit (GPU), which has been applied successfully in many areas for parallel computing. Simulation results show the effectiveness of the OO method and the power of GPU for parallel computing. © 2012 IEEE.

关键词： Graphics processing unit

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Biped robot push detection and recovery

Biped robot push detection and recovery

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International Conference on Information and Automation (ICIA)

作者： Awais Yasin Qiang Huang Qian Xu Weimin Zhang Key Laboratory of Biomimetic Robots and Systems Key Laboratory of Intelligent Control & Decision of Complex Systems Intelligent Robotics Institute School of Mechatronics Engineering Beijing Institute of Technology Beijing P.R. China

This paper presents a balance control approach for a biped robot by regulating COM position with the help of proper foot placement in response to external perturbation. The proposed approach detects present postural and stability state of robot through sensory data from Attitude and Heading Reference System (AHRS) and foot force sensors; and in case of external push, recovers the balance and posture of the robot by foot placement in appropriate direction. The foot placement is carried out using one of the alternative or rescue trajectories already available in the memory of the robot. The rescue trajectories are developed for both sagittal and lateral plane and the strategy for switching from current trajectory to the rescue trajectory and then back to the normal trajectory is discussed in detail. The proposed balance recovery approach is then implemented on a biped robot and is experimentally verified.

关键词： Trajectory Legged locomotion Robot sensing systems Foot Robot kinematics Current measurement

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A GPU based trafficparallel simulation module of artificial transportation systems

A GPU based trafficparallel simulation module of artificial ...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

ISBN: (纸本)9781467324007

Traffic micro-simulation is an important tool in the intelligent Transportation systems (ITS) research. In the micro-simulation, a bottom up system can be built up by the interactions of vehicle agents, road agents, traffic lights agents, etc. The Artificial societies, Computational experiments, and Parallel execution (ACP) approach suggests integrating other metropolitan systems such as logistic, infrastructure, legal and regulatory, weather and environmental systems to build an Artificial Transportation System (ATS) to help solve ITS problems. This is reasonable as the transportation system is complex that is affected by many systems interacting with each other. However, there is a challenge that the computing burden can be very heavy as there can be many agents of different kinds interacting in parallel in ATS. 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 a parallel traffic simulation module of ATS with GPU. The simulation results are reasonable and a maximum speedup factor of 105 is obtained compared with the CPU implementations. © 2012 IEEE.

关键词： Graphics processing unit

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ACP based 3D emergency drills system for petrochemical plants

ACP based 3D emergency drills system for petrochemical plant...

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10th World Congress on intelligent control and Automation, WCICA 2012

作者： Jing, Sifeng Cheng, Changjian Xiong, Gang Liu, Xiwei Shang, Xiuqin Wang, Weixing State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China Dongguan Research Institute of CASIA Cloud Computing Industrial Technology Innovation and Incubation Center Chinese Academy of Sciences Songshan-Lake 523808 China

ISBN: (纸本)9781467313988

To further enhance emergency management skills of an organisation's emergency response personnel, emergency response training,especially 3D emergency drill, is currently becoming more and more important in the petrochemical sector. So, a novel 3D emergency drills system is designed and developed based on ACP approach, which can be used for mocking emergency response plan drills and evaluating the plan. A case study reveals that the performance of the system is good and the system can meet the needs of emergency response training and optimizing emergency response plan in petrochemical plants. © 2012 IEEE.

关键词： Personnel training

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Fuzzy-Neural Networks for a piloted Quality Management System

Fuzzy-Neural Networks for a piloted Quality Management Syste...

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Mediterranean Electrotechnical Conference (MELECON)

作者： Hajer Ben Mahmoud Dammak Raouf Ketata Taieb Ben Romdhane Samir Ben Ahmed National Institute of Applied Science and Technology Tunis Tunisia Research units on Methods and tools for Complex Computer Systems (MOSIC) Tunis Tunisia Research units on Intelligent Control design and Optimization of Complex System (ICOS) Tunis Tunisia

The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management System (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex.

关键词： Fuzzy neural networks Quality management Computational modeling Classification algorithms Biological system modeling Unified modeling language

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Leader-follower synchronization for complex dynamical networks via sampled-data control

Leader-follower synchronization for complex dynamical networ...

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31st Chinese control Conference, CCC 2012

作者： Wangli, He Feng, Qian Han, Qing-Long Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China Centre for Intelligent and Networked Systems Central Queensland University Rockhampton QLD 4702 Australia School of Information and Communication Technology Central Queensland University Rockhampton QLD 4702 Australia

ISBN: (纸本)9789881563811

This paper is concerned with leader-follower synchronization of complex dynamical networks with sampled-data control. By sampling the signal from the leader at some discrete time instants and using a zero-order hold function, synchronization is achieved between the network and a desired orbit, known as the leader. By applying Lyapunov functional approach and the property of the network topology matrix, a delay-dependent criterion is derived. It is shown that synchronization of N coupled dynamical systems with a leader can be recast into the stability of N decoupled systems, in which eigenvalues of the network topology matrix are involved. Finally, a chaotic neural network is used to illustrate the effectiveness of the proposed method. © 2012 Chinese Assoc of Automati.

关键词： Synchronization

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Leader-follower synchronization for complex dynamical networks via sampled-data control

Leader-follower synchronization for complex dynamical networ...

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Chinese control Conference

作者： Wangli He Feng Qian Qing-Long Han The Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Centre for Intelligent and Networked Systems Central Queensland University

ISBN: (纸本)9781467325813

关键词： Synchronization Sampled-data control complex networks

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A weighted pattern recognition algorithm for short-term traffic flow forecasting

A weighted pattern recognition algorithm for short-term traf...

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IEEE International Conference on Networking, Sensing and control

作者： Shuangshuang Li Zhen Shen Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Beijing Engineering Research Center for Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China

The k-nearest neighbor (k-NN) nonparametric regression is a classic model for single point short-term traffic flow forecasting. The traffic flows of the same clock time of the days are viewed as neighbors to each other, and the neighbors with the most similar values are regarded as nearest neighbors and are used for the prediction. In this method, only the information of the neighbors is considered. However, it is observed that the “trends” in the traffic flows are useful for the prediction. Taking a sequence of consecutive time periods and viewing the a sequence of “increasing”, “equal” or “decreasing” of the traffic flows of two consecutive periods as a pattern, it is observed that the patterns can be used for prediction, despite the patterns are not from the same clock time period of the days. Based on this observation, a pattern recognition algorithm is proposed. Moreover, empirically, we find that the patterns from different clock time of the days can have different contributions to the prediction. For example, if both to predict the traffic flow in the morning, the pattern from the morning can lead to better prediction than same patterns from afternoon or evening. In one sentence, we argue that both the pattern and the clock time of the pattern contain useful information for the prediction and we propose the weighted pattern recognition algorithm (WPRA). We give different weights to the same patterns of different clock time for the prediction. In this way, we take both virtues of the k-NN method and the PRA method. We use the root mean square error (RMSE) between the actual traffic flows and the predicted traffic flows as the measurement. By applying the results to actual data and the simulated data, about 20% improvement compare with the PRA is obtained.

关键词： Clocks Data models Pattern recognition Prediction algorithms Mathematical model Meteorology Vectors

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