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International Conference on Natural Computation (ICNC)

作者： Chengyun Liu Zhenxue Chen Faliang Chang Kaifang Wang Key Laboratory of Intelligent Computing & Signal Processing Anhui University Hefei P. R. China School of Control Science & Engineering Shandong University Jinan P. R. China Jiangsu Key Laboratory of Image and Video Understanding for Social Safety Nanjing University of Science and Technology Nanjing P. R. China

ISBN: (纸本)9781479951529

Face recognition is one of typical biometric identification method, which has a great prospect in secure authentication system, file management, human-computer interaction and social security. This paper proposes gray-scale characteristics and creates facial templates to recognize faces method based on a given number of samples. Firstly, it selects the method of building template according to the number of samples to create the facial template image; then, it will compare the difference of first-order edge entropy between recognition image and the template image and find the best match result; finally, the recognition result is output. Experimental results show that the proposed algorithm has good recognition effect on face recognition under non-constraint conditions.

关键词： Face recognition Face Entropy Lighting image edge detection

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An Anti-interfering Reconstruction Algorithm Based on Compressed Sensing

An Anti-interfering Reconstruction Algorithm Based on Compre...

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2013 3rd International Conference on Electric and Electronics(EEIC 2013)

作者： Mei Du Huaici Zhao Chunyang Zhao Bo Li Shenyang Institute of automation Chinese Academy of Science University of Chinese Academy of Sciences Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision

When images compressed by traditional transformation-based compression algorithms are transmitted over wireless channels, if the gaussian random interference causes the loss of the crucial transformation coefficients, the contents of the reconstructed images will be lost obviously and this will reduce the accuracy of the subsequent detection and recognition results greatly. In order to solve this problem, this paper proposed an antiinterfering image reconstruction algorithm based on compressed sensing. This algorithm first confirmed the new compressed sensing signals and the new reconstruction matrix based on the locations of the compressed sensing signal components corresponding to the gaussian-interfered bit stream, and then reconstructed the original images employing the iterative threshold algorithm. The simulation results demonstrated that the new algorithm reconstructed exact images at low bit error rates, and reconstructed inexact images whose qualities were slightly lowered without loss of local contents at high bit error rates. As a result, our algorithm is able to overcome the deficiencies of compression algorithms based on diverse transformations and the iterative threshold algorithm, thus proposes a feasible solution scheme for the anti-interfering problem that arises in wireless image transmission.

关键词： anti-interference compressed sensing image reconstruction Gaussian random interference

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The Infrared Multispectral image Simulation Research Based on 3D Scene

The Infrared Multispectral Image Simulation Research Based o...

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2013 3rd International Conference on Electric and Electronics(EEIC 2013)

作者： Bo Li Huai-ci Zhao Mei Du Jinfeng Lv Department of Optical-Electronics and Information Processing Shenyang Institute of automation Chinese Academy of Science University of Chinese Academy of Science Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Science Key Laboratory of Image Understanding and Computer Vision Shenyang Institute of Engineering

A method of generating infrared multispectral simulation images by 3D scene is presented. The infrared images at any observation angle of the scene and a data cube of simulation images of specific waveband could be generated by the method. Some experiments have been done in waveband 3～5μm to generate a data cube involving 401 infrared simulation images in the wavelength step 0.005μm, and the experiments results show that the simulation method presented in this paper could generate infrared multispectral images data cube rapidly. A way to reflect the differences while the observation angle changed is mentioned in this paper.

关键词： infrared multispectral simulation the data cube self-radiation

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Variable structure multiple model for articulated human motion tracking from monocular video sequences

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Science China(Information Sciences) 2012年第5期55卷 1138-1150页

作者： HAN Hong 1,TONG MingLei 2,CHEN ZhiChao 1 & FAN YouJian 1 1 key laboratory of Intelligent Perception and image understanding of Ministry of Education of China,Institute of Intelligent Information processing,Xidian University,Xi'an 710071,China 2 School of Computer and Information Engineering,Shanghai University of Electric Power,Shanghai 200090,China 1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi’an 710071 China2. School of Computer and Information Engineering Shanghai University of Electric Power Shanghai 200090 China

A new model-based human body tracking framework with learning-based theory is introduced in this *** propose a variable structure multiple model (VSMM) framework to address challenging problems such as uncertainty of motion styles,imprecise detection of feature points,and ambiguity of joint *** human joint points are detected automatically and the undetected points are estimated with Kalman *** motion models are learned from motion capture data using a ridge regression *** model set that covers the total motion set is designed on the basis of topological and compatibility relationships,while the VSMM algorithm is used to estimate quaternion vectors of joint *** using real image sequences and simulation videos demonstrate the high efficiency of our proposed human tracking framework.

关键词： human motion tracking ridge regression model groups design variable structure multiple model (VSMM) motion model group adaptation

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image denoising with non-local means in the shearlet domain

Image denoising with non-local means in the shearlet domain

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International Workshop on Multi-Platform/Multi-Sensor Remote Sensing and Mapping

作者： Zhang, Xiaohua Zhang, Qiang Jiao, L.C. Key Laboratory of Intelligent Perception and Image Understanding Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

ISBN: (纸本)9781424494040

In this paper, a novel method for image denoising is proposed which adopts multiscale geometry tool. Firstly the image is decomposed by discrete shearlet transform. The shearlet coefficients of each direction approach the generalized Gaussian distribution. We use the principal component analysis (PCA) for every similarity window of shearlet coefficients. Then we use Generalized Gaussian model of non-local means method to handle the shearlet coefficients. Finally, we reconstruct image with the new shearlet coefficients to obtain the result. Numerical results show that our algorithm competes favorably with nonlocal means algorithms in the case of high noise. ©2011 IEEE.

关键词： Principal component analysis

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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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Accelerated algorithm to incomplete nonnegative matrix factorization

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Tien Tzu Hsueh Pao/Acta Electronica Sinica 2011年第2期39卷 291-295页

作者： Shi, Jia-Rong Jiao, Li-Cheng Shang, Fan-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an Shaanxi 710071 China

Nonnegative matrix factorization (NMF) is an increasingly popular technique for data processing and analysis. For an incomplete data matrix, the weighted nonnegative matrix factorization (WNMF) is employed to decompose it. But the searching step size in WNMF is not optimal along the given searching direction. This paper studies the incomplete nonnegative matrix factorization (INMF) and proposes an accelerated algorithm. First, INMF is transformed into solving alternatively two nonnegative least squares (NNLS) problems. For each NNLS problem, the exact step size is chosen along the searching direction. Then, the complexity of NNLS problems is analyzed. Finally, experimental results show that the proposed method outperforms WNMF.

关键词： Matrix algebra

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Nondominated individual selection strategy based on adaptive partition for evolutionary multi-objective optimization

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Jisuanji Yanjiu yu Fazhan/Computer Research and Development 2011年第4期48卷 545-557页

作者： Gong, Maoguo Cheng, Gang Jiao, Licheng Liu, Chao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xidian University Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

Many real world problems involve the simultaneous optimization of various and often conflicting objectives. These optimization problems are known as multi-objective optimization problems. Evolutionary multi-objective optimization, whose main task is to deal with multi-objective optimization problems by evolutionary computation techniques, has become a hot topic in evolutionary computation community. The solution diversity of multi-objective optimization problems mainly focuses on two aspects, breadth and uniformity. After analyzing the traditional methods which were used to maintain the diversity of individual in multi-objective evolutionary algorithms, a novel nondominated individual selection strategy based on adaptive partition is proposed. The new strategy partitions the current trade-off front adaptively according to the individual's similarity. Then one representative individual will be selected in each partitioned regions for pruning nondominated individuals. For maintaining the diversity of the solutions, the adaptive partition selection strategy can be incorporated in multi-objective evolutionary algorithms without the need of any parameter setting, and can be applied in either the parameter or objective domain depending on the nature of the problem involved. In order to evaluate the validity of the new strategy, we apply it into two state-of-the-art multi-objective evolutionary algorithms. The experimental results based on thirteen benchmark problems show that the new strategy improves the performance obviously in terms of breadth and uniformity of nondominated solutions.

关键词： Multiobjective optimization

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Concatenated edge and co-occurrence feature extracted from Curvelet Transform for human detection

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Journal of Information and Computational Science 2011年第4期8卷 662-670页

作者： Han, Hong Fan, Youjian Jiao, L.C. Chen, Zhichao Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China

An efficient feature extraction method based on the Curvelet Transform for detecting human in static images is proposed in this paper. The edge features can be extracted with the block-based statistical information of each sub-band coefficients, and then the texture feature can be extracted from the co-occurrence matrixes of the lowest-frequency sub-band coefficients, all the extracted features are concatenated as the final feature vector of the images. All the training and test data are from the INRIA and MIT human dataset. The classification results with test data show that the proposed feature extraction method is suitable for human detection. From the detection results, it can be seen that, the detection accuracy of the proposed method is higher, meanwhile the false positive rate is lower than the Histograms of Oriented Gradients (HOG) method. Copyright © 2011 Binary Information Press.

关键词： Feature extraction

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Semantic segmentation using regions in natural scenes

Semantic segmentation using regions in natural scenes

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2011 International Conference on Electronic and Mechanical Engineering and Information Technology, EMEIT 2011

作者： Wu, Shilin Zhu, Feng Hao, Yingming Shenyang Institute of Automation Chinese Academy of Sciences Shenyang 110016 China Graduate School Chinese Academy of Sciences Beijing 100049 China Key Laboratory of Optical-Electronics Information Processing Chinese Academy of Sciences Shenyang 110016 China Key Laboratory of Image Understanding and Computer Vision Liaoning Province 110016 China

ISBN: (纸本)9781612840857

By introducing an over-segmentation algorithm into the conditional model (CM), we propose a new region-based CM model (R-CM), and investigate its performance on semantic segmentation of images. In order to incorporate structure information of objects, we segment an image into regions by using an over-segmentation algorithm. Based on the results of CM model, we first consider assigning all pixels in one region with the same label, and then other feature potentials are included to counteract the influence of false over-segmentation. We compare our results to related work on the Olive & Torralba database and show that aside from improved accuracy of the whole database, our model obtains a perceptual improvement, with boundary of different objects correctly labeled. © 2011 IEEE.

关键词： Semantic Segmentation

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