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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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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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Research on fuzzy enhancement in the diagnosis of liver tumor from B-mode ultrasound images

Research on fuzzy enhancement in the diagnosis of liver tumo...

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

作者： Qiu, Wu Wang, Rui Xiao, Feng Ding, Mingyue School of Life Science and Technololgy Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan Hubei China

ISBN: (纸本)9780769546230

Fuzzy enhancement is applied in computer aided diagnosis of liver cancer from B mode ultrasound images as a pre-processing procedure in this paper. It was evaluated with three classifiers including K means, back propagation neural network and support vector machine using 25 features from first order statistic (FOS), gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), Grey level dependant matrix (GLDM) and LAWS. In the analysis of 166 normal liver tissue, 30 hemangioma and 60 malignant tumor, our method improved the classification accuracy of three classifiers (K means, BP neural network and support machine vector) in distinguishing liver cancer, hemangioma and normal liver cancer from B mode ultrasound images. It is proved that fuzzy enhancement as an efficient preprocessing procedure could be used in the computer aided diagnosis system of liver cancer. © 2011 IEEE.

关键词： Support vector machines

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Deformation prediction of landslide based on genetic-simulated annealing algorithm and BP neural network

Deformation prediction of landslide based on genetic-simulat...

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4th International Workshop on Advanced Computational Intelligence, IWACI 2011

作者： Chen, Huangqiong Zeng, Zhigang Department of Control Science and Engineering Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074 China

ISBN: (纸本)9781612843735

In this paper, a modified method for landslide prediction is presented. This method is based on the back propagation neural network(BPNN), and we use the combination of genetic algorithm and simulated annealing algorithm to optimize the weights and biases of the network. The improved BPNN modeling can work out the complex nonlinear relation by learning model and using the present data. This paper demonstrates that the revised BPNN modeling can be used to predict and calculate landslide deformation, quicken the learning speed of network and improve the predicting precision. Applying this thinking and method into research of some landslide in the Three Gorges reservoir, the validity and practical value of this model can be demonstrated. And it also shows that the dynamic prediction of landslide deformation is very crucial. © 2011 IEEE.

关键词： Landslides

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Feature extraction of motor imagery EEG signals based on wavelet packet decomposition

Feature extraction of motor imagery EEG signals based on wav...

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IEEE/Institute of Complex Medical Engineering International Conference on Complex Medical Engineering

作者： Hu, Dingyin Li, Wei Chen, Xi Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Engineering Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9781424493241

Feature extraction in brain-computer interface (BCI) work is an important task that significantly affects the success of brain signal classification. In this paper, a feature extraction method of electroencephalographic (EEG) signals based on wavelet packet decomposition (WPD) is used. The coefficients mean of wavelet packet decomposition and wavelet packet energy of special sub-bands are employed as the original features. The Fisher discriminant analysis (FDA) is used to measure the separabilities of those features. The features which had a higher separability will be considered as effective ones and then the final feature vector are formed. A feature vector is obtained by combining the selected features from six channels. Then, the features are classified by using the k-nearest neighbor (k-NN) algorithm. We obtained significant improvement for the speed and accuracy of the classification for data set Ia, which is a typical representative of one kind of BCI competition 2003 data. The classification results have proved the effectiveness of the proposed method. © 2011 IEEE.

关键词： Feature extraction

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ANN-based control method implemented in a Voltage Source Converter for industrial Micro-Grid

ANN-based control method implemented in a Voltage Source Con...

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

作者： Xu, Jinbang Wu, Zhizhuo Yang, Xuan Ye, Jie Shen, Anwen Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Department of Control Science and Technology Huazhong University of Science and Technology 430074 Wuhan China

ISBN: (纸本)9780769545141

With more and more attention on the grid current harmonic in recent years, many control schemes of the Pulse Width Modulation Voltage Source Converter (PWMVSC) have been investigated. Conventional PI controller has shown limitations such as sensitivity to load and system parameter variation. Even the stability of the system can be threatened under a large and sudden load change. In this paper, the practical situation of a VSC for industrial Micro Grid (MG) is considered and an Artificial neural network (ANN) based control method is employed to solve the problem. Meanwhile, an on-line parameter tuning algorithm is introduced for its advantage of self-tuning and system character identification. The proposed control scheme is verified through simulation based on SABER software. The simulation results have shown the advantage of the proposed method and the performance of the parameter tuning session. © 2011 IEEE.

关键词： Neural networks

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A Traffic Flow Detection System Combining Optical Flow and Shadow Removal

A Traffic Flow Detection System Combining Optical Flow and S...

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第三届全国智能视觉监控学术会议

作者： Yunhong Wang Zhaoxiang Zhang Yuqing Hou Jie Qin 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 MediaB

ISBN: (纸本)9781457718342

Traffic flow detection plays an important role in intelligent Transportation Systems(ITS).Video based traffic flow detection system is the most widely used strategy in *** this circumstance,we design and implement a video based traffic flow detection system which is called MyTD in this *** takes advantages of both shadow removal and optical flow ***,we introduce the current development of ITS and focus on the video based traffic detection technology,which is the key to ***,a shadow removal algorithm combining information in both RGB and HSV color spaces is ***,based on the Iterative Pyramidal LK Optical Flow Algorithm,a vehicle tracking function is realized by OpenCV,as well as a Connected Components Labeling function and the vehicle counting ***,MyTD is implemented and tested based on the algorithm presented *** results show the outstanding performance of our method comparing with traditional optical flow algorithms.

关键词： Optic Flow Traffic flow Videotapes Detection systems connected component shadows red-green-blue colour model intelligent Tutoring Systems intelligent transportation systems

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New method for improving the performance of SAR image segmentation

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Dianzi Yu Xinxi Xuebao/Journal of Electronics and Information Technology 2011年第7期33卷 1700-1705页

作者： Yan, Xue-Ying Jiao, Li-Cheng Wang, Ling-Xia Wan, Hong-Lin Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

Considering the shortage of edge preservation and low direction-resolution for SAR image segmentation based on the conventional wavelet transform domain, a new segmentation method is proposed based on Gray-Level Cooccurrence Probability (GLCP) features in the overcomplete Brushlet domain. This method compresses the redundant GLCP features extracted by the adaptive window Gabor filtering in different direction coefficient blocks using compressed sensing, then the Fuzzy C-Mean (FCM) clustering method is utilized to complete the clustering and obtain the segmentation result. The experiment results show that the new method has advantages in the edge preservation and direction extraction, and obtains better segmentation results with respect to other methods.

关键词： Gabor filters

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