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International Conference on Pattern Recognition

作者： Shuang Liu Chunheng Wang Baihua Xiao Zhong Zhang Yunxue Shao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467322164

Traditional sparse coding has been successfully applied in texture and image classification in the past years. Yet such kind of method neglects the influence of the signs of coding coefficients, which may cause information loss in the sequential max pooling. In this paper, we propose a novel coding strategy for ground-based cloud classification, which is named soft-signed sparse coding. In our method, a constraint on the signs is explicitly added to the objective function of traditional sparse coding model, which can effectively regulate the ratio between the number of positive and negative non-zero coefficients. As a result, the proposed method can not only obtain low reconstruction error but also consider the influence of the signs of coding coefficients. The strategy is verified on two challenging cloud datasets, and the experimental results demonstrate the superior performance of our method compared with previous ones.

关键词： Encoding Image coding Clouds Dictionaries Vectors Image reconstruction Linear programming

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Heuristic dynamic programming-based H∞ control of discrete-time affine nonlinear systems

Heuristic dynamic programming-based H∞ control of discrete-...

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International Conference on Intelligent control and Information Processing (ICICIP)

作者： Hongliang Li Derong Liu Ding Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In this paper, we solve the H ∞ control problems for discrete-time affine nonlinear systems with known dynamics. An iterative heuristic dynamic programming algorithm is derived and the convergence analysis is provided. Three neural networks are used to approximate the control policy, the disturbance policy, and the value function, respectively. A simulation example is presented to demonstrate the effectiveness of the proposed scheme.

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Contextual Fisher kernels for human action recognition

Contextual Fisher kernels for human action recognition

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International Conference on Pattern Recognition

作者： Zhong Zhang Chunheng Wang Baihua Xiao Wen Zhou Shuang Liu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In the literature of human action recognition, despite promising results have been obtained by the traditional bag-of-words model, the relationship among spatiotemporal points has rarely been considered. Furthermore, serious quantization error also exists in this kind of strategy. In this paper, we propose a novel coding strategy named contextual Fisher kernels to overcome these limitations. We add a Gaussian function to represent contextual information into the generative model. In this way, our method explicitly considers the spatio-temporal contextual relationships between interest points and alleviates quantization error. Our method is verified on two challenging datasets (KTH and UCF sports), and the experimental results demonstrate that our method achieves better results than the state-of-the-art methods in human action recognition.

关键词： Kernel Humans Context modeling Quantization Vectors Accuracy Covariance matrix

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Parallel public transport management and control system for Guangzhou Asian Games

Parallel public transport management and control system for ...

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IEEE International Conference on Networking, Sensing and control

作者： Xisong Dong Gang Xiong Dong Fan Fenghua Zhu Yisheng Lv State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Public traffic is required for the convenient travel, reducing traffic congestion and accidents, low-carbon, environmental protection, sustainable development, and traffic demand of giant sports and large business activities, etc. For public transport demand of the 16th Asian Games and the 2010 Asian Para Games held in Guangzhou in 2010, based on ACP approach, Parallel Public Transport management And control System (PPTMS) for Guangzhou Asian Games had been developed to support management decision of public transport. This system can help public transport managers to improve and enhance significantly the level of public transport management in Guangzhou, from experience-based formulation and manual implementation to scientific computation-based formulation and automatic implementation with intelligent systems, to guarantee the traffic demand effectively during the two Games.

关键词： Games Indexes Vehicles Streaming media Security Accidents

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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 hierarchical networked urban traffic signal control system based on multi-agent

A hierarchical networked urban traffic signal control system...

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IEEE International Conference on Networking, Sensing and control

作者： Cheng Chen Zheng Jiang Li State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

In this paper, we proposed an architecture of a hierarchical networked urban traffic signal control system Based on Multi-agent. With mobile agent technology, traffic control strategies are designed as traffic control agents, which can move from device to device in a network. The system can reconfigure and replace these agents according to inconstant states of traffic environment and performances of agents. By this way, demand-based control is realized in traffic signal control system. Then we described the details and key technologies in the procession of agent-generation, agent-storage and agent-usage. At last, a prototype of the system is developed and basic functions of this system are tested by simulations. These simulations also confirm extensibility and effectiveness of the system.

关键词： control systems Databases Organizations Vehicles Roads Mobile communication Aerospace electronics

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Adaptive Graph Cut Based Binarization of Video Text Images

Adaptive Graph Cut Based Binarization of Video Text Images

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IAPR International Workshop on Document Analysis systems, DAS

Interactive image segmentation which needs the user to give certain hard constraints has shown promising performance for object segmentation. In this paper, we consider characters in text image as a special kind of object, and propose an adaptive graph cut based text binarization method to segment text from background. The main contributions of the paper lie in: 1) in order to make the binarization local adaptive with uneven background, the text region image is firstly roughly split into several sub-images on which graph cut is applied, and 2) considering the unique characteristics of the text, we propose to automatically classify some pixels as text or background with high confidence, severed as hard constraints seeds for graph cut to extract text from background by spreading the seeds into the whole sub-image. The experimental results show that our approach could get better performance in both character extraction accuracy and recognition accuracy.

关键词： Image segmentation Image color analysis Image edge detection Character recognition Optical character recognition software Noise

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Training Strategies for a Lower Limb Rehabilitation Robot Based on Impedance control

Training Strategies for a Lower Limb Rehabilitation Robot Ba...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society

作者： Jin Hu Zengguang Hou Feng Zhang Yixiong Chen Pengfeng Li State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781424441198

This paper proposes three training strategies based on impedance control, including passive training, damping-active training and spring-active training, for a 3- DOF lower limb rehabilitation robot designed for patients with paraplegia or hemiplegia. controllers with similar structure are developed for these training strategies, consisting of dual closed loops, the outer impedance control loop and the inner position/ velocity control loop, known as position-based impedance control method. Simulation results verify that position-based impedance control approach is feasible to accomplish the training strategies.

关键词： Training Strategies Lower Limb Rehabilitation Robot Based Impedance control

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Sparse Representation based on Matrix Rank Minimization and K-Means Clustering for Recognition

Sparse Representation based on Matrix Rank Minimization and ...

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International Joint Conference on Neural Networks

作者： Long Ma Chunheng Wang Baihua Xiao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 100190

ISBN: (纸本)9781467314886

In this paper, we propose a sparse coding algorithm based on matrix rank minimization and k-means clustering and for recognition. We consider the problem of removing the noise in the training samples and generating more samples at the same time. To accomplish this, we extended the matrix rank minimization problem to cope with complex data. Samples from the same class are segmented into several groups by k-means clustering algorithm, and matrix rank minimization is applied on the clustered data to separate the noises and recover the low-rank structures in the grouped data. An over-complete dictionary is constructed by connecting the low-rank structures and the training samples together to keep the samples diversity. Sparse representation is operated based on this over-complete dictionary for recognition. Furthermore, a parameter is introduced to adjust the weighting of the coefficients that code the noises. We apply the proposed algorithm for character and face recognition. Experiments with improved performances validate the effectiveness of the proposed algorithm.

关键词： sparse representation Noise Recognition (Psychology) Rank of data matrices Sparse coding Dictionaries as Topic

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Application of feature matching in the vehicle violation detection in urban traffic

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content Technology and its Applications 2012年第11期6卷 131-138页

作者： Ding, Huan Liu, Jin Zhao, Bo Zhang, Wensheng Dong, Wenyong State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Computer School Wuhan University China

Computer vision and video analytics become increasingly important for intelligent transport systems (ITSs), and violation detection is one of the key points in ITSs. It is widely recognized that image based systems are flexible and versatile for advanced traffic monitoring and enforcement applications. In the proposed method, we first locate the tails from the images captured by a stationary camera, and then SURF(Speeded Up Robust Features) feature points are extracted from these tail images. A matching based rough detection stage is taken place to identify the high risk tails which are seen as violations and the low risk tails which are omitted as regular vehicles. Finally, color and shape information are taken advantages of to accomplish violation detection in the undetermined vehicles in the previous stage. Experiments are conducted using real live video sequences captured from an urban cross road. Results show that our method can potentially have a good performance.

关键词： Vehicles

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