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Tuning of Auto-Disturbance Rejection controller based on the invasive weed optimization

Tuning of Auto-Disturbance Rejection Controller based on the...

引用

6th International Conference on Bio-Inspired Computing: Theories and Applications, BIC-TA 2011

作者： Chen, Zhihua Wang, Shuo Deng, Zhonghua Zhang, Xuncai Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 Hubei China School of Electrical and Electronic Engineering Zhengzhou University of Light Industry Zhengzhou 450002 China

ISBN: (纸本)9780769545141

Auto-Disturbance Rejection controller (ADRC) has been proved to be a capable replacement of PID with unmistakable advantage in performance and practicality. But it is difficult to obtain a set of optimal parameters, for ADRC controller has too many parameters and has no deterministic rules to compute the parameters. In this paper, Objective function is constructed based on the control system performance indexes. Combined with experienced parameters of ADRC, an invasive weed optimization algorithm (IWO) is employed to obtain a set of key parameters. The simulation results show the validity of the IWO algorithm. © 2011 IEEE.

关键词： Invasive weed optimization

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Interesting Region Detection in Aerial Video Using Bayesian Topic Models

Interesting Region Detection in Aerial Video Using Bayesian ...

引用

第一届亚洲模式识别会议

作者： Jiewei Wang Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Searching interesting regions in aerial video is a new and challenging problem. This paper presents an approach to detect visual interesting regions in aerial video using pLSA topic model. Traditional interesting region detection approaches just use bottom-up information, such as color, orientation and movement etc. Our proposed method can discover the semantic content of the whole image, the co-occurrence of local image patches via pLSA model, and consequently improve detection result significantly in real world scenes. First, we extract frames from aerial video as documents. Then we use vector quantized SIFT descriptors as words. Third, we discover topics (e.g. plants, roads, buildings) and the relation among them using pLSA model. Finally, we can detect interesting regions as we need according to calculated models. Experimental observations show the success of our approach on interesting region detection in aerial video.

关键词： Visualization Histograms Detectors Semantics Observers Vectors Vocabulary

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Saliency Model Based Head Pose Estimation by Sparse Optical Flow

Saliency Model Based Head Pose Estimation by Sparse Optical ...

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第一届亚洲模式识别会议

作者： Chao Wang Tao Xu Yunhong Wang Zhaoxiang Zhang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

Head pose plays an important role in Human- Computer interaction, and its estimation is a challenge problem compared to face detection and recognition in computer vision. In this paper, a novel and efficient method is proposed to estimate head pose in real-time video sequences. A saliency model based segmentation method is used not only to extract feature points of face, but also to update and rectify the location of feature points when missing happened. This step also gives a benchmark for vector generation in pose estimation. In subsequent frames feature points will be tracked by sparse optical flow method and head pose can be determined from vectors generated by feature points between successive frames. Via a voting scheme, these vectors with angle and length can give a robust estimation of the head pose. Compared with other methods, annotated training data set and training procedure is not essential in our method. Initialization and re-initialization can be done automatically and are robust for profile head pose. Experimental results show an efficient and robust estimation of the head pose.

关键词： Face Estimation Magnetic heads Optical imaging Computer vision Skin

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Multi-view Moving Objects Classification via Transfer Learning

Multi-view Moving Objects Classification via Transfer Learni...

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第一届亚洲模式识别会议

作者： Jianyun Liu Zhaoxiang Zhang Yunhong Wang Yi Mo Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Moving objects classification in traffic scene videos is a hot topic in recent years. It has significant meaning to intelligent traffic system by classifying moving traffic objects into pedestrians, motor vehicles, non-motor vehicles etc.. Traditional machine learning approaches make the assumption that source scene objects and target scene objects share same distributions, which does not hold for most occasions. Under this circumstance, large amount of manual labeling for target scene data is needed, which is time and labor consuming. In this paper, we introduce TrAdaBoost, a transfer learning algorithm, to bridge the gap between source and target scene. During training procedure, TrAdaBoost makes full use of the source scene data that is most similar to the target scene data so that only small number of labeled target scene data could help improve the performance significantly. The features used for classification are Histogram of Oriented Gradient features of the appearance based instances. The experiment results show the outstanding performance of the transfer learning method comparing with traditional machine learning algorithm.

关键词： Feature extraction Training image edge detection Training data Accuracy Videos Support vector machines

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A Real Time Object Tracking Approach for Mobile Robot Visual Servo control

A Real Time Object Tracking Approach for Mobile Robot Visual...

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第一届亚洲模式识别会议

作者： Zhaoxiang Zhang Yunhong Wang Ruhan Sa Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

A key problem of image Based Visual Servo (IBVS) System is to track objects in image sequences. Thus, the tracking algorithm plays an important role in improving the efficiency of IBVS systems. In this paper, a novel tracking algorithm called Modified CamShift Guided Particle Filter (MCAMSGPF) is proposed, which interpolated Speeded-Up Robust Features (SURF) into the framework of conventional CamShift Guided Particle Filter (CAMSGPF) tracking method. This new algorithm outperforms conventional CAMSGPF and other baseline trackers with respect to tracking robustness in the clutter background of similar colors and occlusions. We also proposed a new system model to implement and test the new algorithm in a real time moving IBVS system, which is applied in a mobile robot with an on-board camera.

关键词： Robustness image color analysis Robots Target tracking Cameras Clutter

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Improving strategies on PSO for suborbit launch vehicle trajectory optimization

Improving strategies on PSO for suborbit launch vehicle traj...

引用

4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Xie, Fuqiang Yang, Ye Chang, Songtao Wang, Yongji School of Electric Engineering University of Souch China Hengyang China Beijing Aerospace Automatic Control Institute Beijing China Department of Control Science and Engineering Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9781612843735

Solving the optimal control problem with a free final time, such as suborbital launch vehicle (SLV) trajectory optimization with two control variables and multi-constraints ones based on particle swarm optimization (PSO), the smoothness of control variable can not be satisfied by linear interpolation method. A novel method including some improving strategies based on PSO for trajectory optimization is proposed, named LCPSO which is a kind of Cooperate PSO based on Legendre orthogonal polynomials. An additional control variable is introduced and transcribes the original optimal problem to a problem with fixed final time, and one dimension searching method based on interval analysis is used to optimize the additional control variable. Furthermore, a theorem on how to find the boundaries of the coefficient of polynomials is proved. Compared with basic PSO, LCPSO has traits of lower dimensions and smoother control variable. An example of trajectory optimization shows the effectiveness of the LCPSO algorithm. © 2011 IEEE.

关键词： Aerodynamics

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View-invariant Action Recognition in Surveillance Videos

View-invariant Action Recognition in Surveillance Videos

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第一届亚洲模式识别会议

作者： Fang Zhang Zhaoxiang Zhang Yunhong Wang Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media Laboratory of Intelligent Recognition and Image Processing Beijing Key Laboratory of Digital Media

ISBN: (纸本)9781457701221

Recently, human action recognition has been a popular and important topic in computer vision. However, except some conventional problems such as noise, low resolution etc., viewinvariant recognition is one of the most challenging problems. In this paper, we focus on solve multi-view action recognition from surveillance video. To detect moving objects from complicated backgrounds, this paper employs improved Gaussian mixed model, which uses K-means clustering to initialize the model and it gets better motion detection results for surveillance videos. We demonstrate the silhouette representation ”Envelope Shape” can solve the viewpoint problem in surveillance videos. The experiment results demonstrate that our human action recognition system is fast and efficient on CASIA activity analysis database.

关键词： Videos Gaussian distribution Surveillance Shape Humans Hidden Markov models Databases

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Quantitative study on despeckle methods of medical ultrasound images

Quantitative study on despeckle methods of medical ultrasoun...

引用

2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Ma, Runxia Zhang, Xuming Ding, Mingyue Liu, Qi Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Electrical Information Engineering Sichuan University Chengdu China

ISBN: (纸本)9780769546230

Speckle is a granular noise that inherently exists in all types of coherent imaging systems. This paper presents a quantitative study on five despeckling methods such as frost filter, kuan filter, speckle reducing an isotropic diffusion, homomorphic filter and wavelet filter. We select six objective evaluation parameters, such as signal-to-ratio, contrast signal-to-noise ratio, figure of merit, least absolute error, edge protection factor, signal-to-minimum mean square error ratio, to quantify the performance of these filters. The comparative study will provide some parameter comparative reference for selecting a suitable filter in the ultrasound image processing. © 2011 IEEE.

关键词： Mean square error

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Steel Billet Recognition in the Heavy Rail Production Line

Steel Billet Recognition in the Heavy Rail Production Line

引用

The International Conference on Automation and Robotics(ICAR 2011)

作者： Hanyu Hong Xiuhua Zhang Yijun Yang Zhejun Yu Laboratory for Image Processing and Intelligent Control Wuhan Institute of Technology

Steel billet recognition is an urgent requirement in the steel industry of heavy rail line. Due to high temperature and complex scene in the rolling line, the recognition at the end of billet is quite different from optical character recognition with simple background and vehicle license plate recognition. In order to solve the problem, this paper presents some new schemes in character location, segmentation and recognition in the complex scene. These proposed algorithms include the location algorithm of multilevel filter based on separability criterion, the segmentation algorithm based on intelligent multiagent and the recognition algorithm of character features matching combining the template matching. The results show that the proposed algorithms are effective for steel billet character recognition in the complex scene.

关键词： Steel billet character character location character segmentation character recognition

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A research of heart rate prediction model based on evolutionary neural network

A research of heart rate prediction model based on evolution...

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2011 IEEE International conference on intelligent Computation and Bio-Medical Instrumentation, ICBMI 2011

作者： Xiao, Feng Yuchi, Ming Ding, Mingyue Jo, Jun Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Life College of Science and Technology Huazhong University of Science and Technology Wuhan China School of Information and Communication Technology Griffith University QLD Australia

ISBN: (纸本)9780769546230

Heart rate (HR) signal analysis is widely used in the medicine and medical research area. Physical activities (PA) are commonly recognized to greatly affect the changes of heart rate. A method of Evolutionary Neural Network - Neuro-evolution of Augmenting Topologies (NEAT) is used to build a PA-based HR predictor model. Through special coding, crossover and mutation operator, NEAT can implement network topology and connectivity weights evolution simultaneously. The common problem in evolutionary neural network, like competing conventions, how to protect the new innovation are effectively solved. The experimental results demonstrated the application potential of the approach. © 2011 IEEE.

关键词： Neural networks

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