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IEEE Conference on Decision and control

作者： Huiyang Liu Guangming Xie Long Wang Center of Systems and Control State Key Laboratory of Turbulence and Complex Systems College of Engineering Peking University Beijing China

ISBN: (纸本)9781424477456

This paper provides consensus analysis for networked continuous-time multi-agent systems via sampled control. The sampled control protocol is induced from a continuous-time consensus protocol by using periodic sampling technology and zero-order hold circuit. Meanwhile, time-varying delay that can be both smaller and larger than the sampling interval is taken into account. Based on graph theory and stability theory, a sufficient condition is proposed to guarantee the consensus achievement under the condition that communication channels suffer from time-varying delay. The main contribution of this paper is to provide a valid distributed consensus algorithm that explicitly describes which state information may be received in the concerning sampling interval. The results are illustrated by some simulations.

关键词： Delay Nickel Multiagent systems Protocols control systems Switched systems Stability analysis

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Stereo Reconstruction Based on Local Edge Detection and Binocular Stereo Matching

Stereo Reconstruction Based on Local Edge Detection and Bino...

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Chinese Conference on Pattern Recognition (CCPR)

作者： Fu He Feipeng Da Key Laboratory of Measurement and Control of Complex System of Ministry of Education Research Institute of Automation South-East University Nanjing China

A stereo reconstruction algorithm is proposed, which combines techniques of local edge detection, stereo matching and binocular vision. Firstly, the left and right images of the object are taken by calibrated binocular cameras. Then, in rectified matching images, the closed local edge is formed surrounding each pixel by Prewitt edge operator in order to construct an adaptive window, in which cost aggregation is calculated by normalized cross-correlation-coefficient. Next, local winner-take-all optimization is used to obtain disparity, and image smoothing technique is introduced to reduce matching errors. Finally, points cloud of the object is produced based on calibration information of binocular cameras and results of stereo matching. The experimental results show that the proposed algorithm can overcome impacts of real environment on reconstruction system and successfully achieves smooth and vivid 3D points cloud models of different real objects with high automation degree.

关键词： Stereo image processing Computer vision Image edge detection Image reconstruction Pattern recognition Conferences

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An improved image segmentation based stereo matching algorithm

An improved image segmentation based stereo matching algorit...

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Chinese Conference on Pattern Recognition

作者： Shao, Jing Da, Feipeng Key Laboratory of Measurement and Control for Complex System of Ministry of Education Research Institute of Automation Southeast University Nanjing 210096 China

ISBN: (纸本)9781424472109

In order to decrease the mismatching problem in low texture and occluded areas, an improved algorithm based on image segmentation is proposed. Firstly, the adaptive polygon-based support window is adopted for initial disparity estimation, then the reliable matching points derived through left-right constraint are used to compute the disparity planes in the segmentation areas;finally the disparity planes are used to constraint the disparity estimation and as a reference of the energy function, then the Tree DP is introduced to compute the optimal disparity for every pixel. In order to testify the validity and practicability of the algorithm, firstly we use it in the matching of the standard images, the experimental results show that our algorithm has a better performance in areas of low texture and occluded areas and a higher matching accuracy, and then the reconstruction results of the real images shows a smooth and valid point cloud model. ©2010 IEEE.

关键词： Image segmentation

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Stereo Matching Based on Dissimilar Intensity Support

Stereo Matching Based on Dissimilar Intensity Support

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Chinese Conference on Pattern Recognition (CCPR)

作者： Fu He Feipeng Da Key Laboratory of Measurement and Control of Complex System of Ministry of Education Research Institute of Automation South-East University Nanjing China

This paper presents a local stereo matching algorithm based on the window construction method using local edge detection. In order to improve performance of window-based cost aggregation computation, a new rule called Dissimilar Intensity Support technique is proposed to distinguish support pixels with dissimilar intensities from those with similar intensity for each centered pixel. According to the proposed rule, support pixels away from centered pixel with dissimilar intensities are used to compute cost aggregation for enhancing intensity variation in local support region. Initial disparity is obtained by classical Winner-Take-All method. Then disparity refinement based on pixels near center with similar intensity as well as smooth disparity is introduced to rectify mismatch. The experimental results based on Middlebury stereo benchmark show that the proposed algorithm has good performance especially in low textured region with only few parameters.

关键词： Pixel Stereo vision Image edge detection Image color analysis Algorithm design and analysis Computer vision Benchmark testing

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3D Face Recognition by Deforming the Normal Face

3D Face Recognition by Deforming the Normal Face

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International Conference on Pattern Recognition

作者： Xiaoli Li Feipeng Da Key Laboratory of Measurement and Control of Complex System of Ministry of Education Research Institute of Automation South-East University Nanjing China

ISBN: (纸本)9781424475421

3D face recognition is complicated by the presence of expression variation. In this paper, we present an automatic 3D face recognition method which can differentiate the expression deformations from the interpersonal differences and recognize faces with expressions being removed. The deformations caused by expression and interpersonal difference are firstly learnt from training set, respectively. Then the deformations are linearly combined to synthesize new face with certain expression. When a target face comes in, the synthesized face is used to match it by adjusting the coefficients in the linear combination. After the matching process, coefficients corresponding to the interpersonal differences are chosen as features for recognition. We perform experiments on the FRGC v2.0 database and good performance is obtained.

关键词： Face Face recognition Training Three dimensional displays Deformable models Feature extraction Iterative closest point algorithm

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An Improved Image Segmentation Based Stereo Matching Algorithm

An Improved Image Segmentation Based Stereo Matching Algorit...

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Chinese Conference on Pattern Recognition (CCPR)

作者： Jing Shao Feipeng Da Key Laboratory of Measurement and Control of Complex System of Ministry of Education Research Institute of Automation South-East University Nanjing China

In order to decrease the mismatching problem in low texture and occluded areas, an improved algorithm based on image segmentation is proposed. Firstly, the adaptive polygon-based support window is adopted for initial disparity estimation, then the reliable matching points derived through left-right constraint are used to compute the disparity planes in the segmentation areas; finally the disparity planes are used to constraint the disparity estimation and as a reference of the energy function, then the Tree DP is introduced to compute the optimal disparity for every pixel. In order to testify the validity and practicability of the algorithm, firstly we use it in the matching of the standard images, the experimental results show that our algorithm has a better performance in areas of low texture and occluded areas and a higher matching accuracy, and then the reconstruction results of the real images shows a smooth and valid point cloud model.

关键词： Stereo vision Image segmentation Signal processing algorithms Belief propagation Estimation Algorithm design and analysis Electronic mail

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Stereo reconstruction based on local edge detection and binocular stereo matching

Stereo reconstruction based on local edge detection and bino...

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Chinese Conference on Pattern Recognition

作者： He, Fu Da, Feipeng Key Laboratory of Measurement and Control for Complex System of Ministry of Education Research Institute of Automation Southeast University Nanjing 210096 China

ISBN: (纸本)9781424472109

A stereo reconstruction algorithm is proposed, which combines techniques of local edge detection, stereo matching and binocular vision. Firstly, the left and right images of the object are taken by calibrated binocular cameras. Then, in rectified matching images, the closed local edge is formed surrounding each pixel by Prewitt edge operator in order to construct an adaptive window, in which cost aggregation is calculated by normalized cross-correlation- coefficient. Next, local winner-take-all optimization is used to obtain disparity, and image smoothing technique is introduced to reduce matching errors. Finally, points cloud of the object is produced based on calibration information of binocular cameras and results of stereo matching. The experimental results show that the proposed algorithm can overcome impacts of real environment on reconstruction system and successfully achieves smooth and vivid 3D points cloud models of different real objects with high automation degree. ©2010 IEEE.

关键词： Binocular vision

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A target tracking algorithm based on mean shift and normalized moment of inertia feature

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Zidonghua Xuebao/Acta Automatica Sinica 2010年第9期36卷 1332-1336页

作者： Gan, Ming-Gang Chen, Jie Wang, Ya-Nan Jin, Dai-Zhong School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Beijing Institute of Technology Beijing 100081 China

The paper presents a target tracking algorithm which is based on the mean shift algorithm and the normalized moment of inertia (NMI) feature, because the result of the moving target tracking in the air is not satisfactory by the traditional mean shift tracking algorithm. The NMI feature of the target is introduced, and the studied tracking strategy based on the minimum principle of the false alarm probability and the two-stage decision threshold of the similarity is constructed in the algorithm. The Kalman filter is used for the estimation and prediction when the target is occluded. The experimental results show that with the algorithm even the moving target in the air is in large deformation and occlusion, the system can effectively guarantee that the tracking is real-time and stable. Copyright © 2010 Acta Automatica Sinica. All rights reserved.

关键词： Kalman filters

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Variable structure neural network adaptive robust control

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Zidonghua Xuebao/ Acta Automatica Sinica 2010年第1期36卷 174-178页

作者： Chen, Jie Li, Zhi-Ping Zhang, Guo-Zhu School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

A variable structure neural network adaptive robust control (VSNNARC) is proposed for a class of uncertain nonlinear SISO systems. A neural network which is adjusted by using nodes activation and passivation techniques to minish the size of the neural network and computation load is used as an opproximator for the system unknown nonlinear functions. And the adaptive robust control is used for the weight learning and compensation to the modeling error and extern disturbances. The adaptation law of neural networks weights and the design method of robust controller are given out based on the Lyapunov stability analysis. Furthermore, the proposed controller can guarantee not only global stability but also transient performance. Finally, the controller is applied to a position tracking system of a turntable. The experimental results show that the system can perform good tracking and has strong robustness. © 2010 Acta Automatica Sinica. All rights reserved.

关键词： controllers

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Adaptive robust dynamic surface control of DC torque motors with true parameter estimates

Adaptive robust dynamic surface control of DC torque motors ...

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American control Conference

作者： Zhiping Li Jie Chen Minggang Gan Hao Fang Guozhu Zhang School of Automation Beijing Institute of Technology and Education Ministry Key Laboratory of Complex Systems Intelligent Control and Decision Beijing China

ISBN: (纸本)9781424474264

This paper presents an adaptive robust dynamic surface control (ARDSC) algorithm for the position control of DC torque motors which are modeled as third-order nonlinear systems with parametric and nonlinear uncertainties. Based on the dynamic surface control (DSC) approach, the "explosion of terms" problem in the normal adaptive robust control (ARC) is avoided, which enhances the practicability of the controller. Furthermore, besides theoretically proving that the tracking error is uniformly ultimate bounded or asymptotically converge to zero in presence of parametric uncertainties only, the true estimates of the unknown parameters are achieved by designing a novel adaptation law, which improves the system performance and can be used in system monitor and diagnosis on-line as byproducts. Finally, the comparative simulation results illustrate that the proposed algorithm is very effective.

关键词： torque motors Position control System performance Parametric Unknown parameter asymptotic Self tuning

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