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International Conference on intelligent Transportation

作者： Mingxia Sun Kunfeng Wang Ming Tang Fei-Yue Wang Jinfeng Yang Tianjin Key Laboratory of Advanced Signal Processing Civil Aviation University of China Tianjin China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences (CAS) Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences (CAS) Beijing China

This paper presents a generic video vehicle detection approach through multiple background-based features and statistical learning. The main idea is to configure several virtual loops (as detection zones) on the image, assuming moving vehicles may cause pixel intensities and local texture to change, and then by identifying such pixel changes to detect vehicles. In this research, multiple pattern classifiers including LDA + Adaboost, SVM, and Random Forests are used to detect vehicles that are passing through virtual loops. We extract fourteen pattern features (related to foreground area, texture change, and luminance and contrast in the local virtual loop zone and the global image) to train pattern classifiers and then detect vehicles. As experimental results illustrate, the proposed approach is quite robust to detect vehicles under complex dynamic environments, and thus is able to improve the accuracy of traffic data collection in all weather for long term.

关键词： Vehicles Feature extraction Training Image edge detection Vehicle detection Meteorology Radio frequency

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Complexity Research of Massively Microblogging Based on Human Behaviors

Complexity Research of Massively Microblogging Based on Huma...

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International Workshop on Database Technology and Applications

作者： Shulong Kang Chuang Zhang Zhiqing Lin Xueming Shi He Ma Pattern Recognition & Intelligent Systems Laboratory (PRIS) Beijing University of Posts and Telecommunications Beijing China

Microblogging is one of the most popular on-line social services by which people can share information and communicate with others. In the paper, it is proved that in a microblogging's social network, there exists small-world, scale-free and high clustering coefficient characteristics, which are three main properties of complex network. It means that microblogging's social network is a complex network. Besides, it is verified that the number of microblogs and the frequency of posting microblogs follow power-law distributions, which is an evidence that shows human dynamics are non-Poissonian. The related geographical property analysis of microblogging's social network illustrates the reason of users' geographical distribution.

关键词： Social network services Humans Complex networks Internet Crawlers Web pages Mobile handsets

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Research on the Parameter Optimal Algorithm of Gaussian Mixture Model in Speaker Identification

Research on the Parameter Optimal Algorithm of Gaussian Mixt...

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Chinese Conference on pattern recognition (CCPR)

作者： Hui Ding Zhenmin Tang Yanping Li Laboratory of Pattern Recognition and Intelligent Systems Nanjing University of Science and Technology of PLA Nanjing Jiangsu China School of Mathematics & Information Engineering Jiaxing University Jiaxing Zhejiang China College of Telecommunications & Information Engineering Nanjing University of Posts and Telecommunications China

In the field of speaker recognition, the Gaussian mixture model with diagonal covariance matrices is a popular technique, in this way, it simplified model and reduced the amount of computation, but lost the correlation information between feature vectors, and then influenced the classification performance. In this paper, in order to compensate the correlation between feature elements, we proposed a novel method based on clustering transformation algorithm, we calculate the similarity between Gaussian components, and the cluster of same components will share one transformation matrix, thus multi-transformation matrices, together with weights and means vectors are obtained simultaneously by maximum likelihood estimation. Theory analysis and experimental results demonstrated that this proposed method can get a better balance between training speed and recognition rate, improve the performance of classifier and reduce the complexity and memory burden relatively.

关键词： Electronic mail Covariance matrix Laboratories pattern recognition intelligent systems Mathematics Educational institutions Speaker recognition Telecommunication computing Clustering algorithms

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Lip Localization on Multi-View Faces in Video

Lip Localization on Multi-View Faces in Video

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Rui Ma Yi Wu Wei Hu Jiaxin Wang Tao Wang Yimin Zhang Hanqing Lu State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy and Sciences China Intel China Research Center Limited Beijing China

In this paper, a real time and robust multi-view lip localization in video frames is proposed. The objective of this research is to exactly localize lip surrounding box with sub-pixel accuracy in low quality video frames. This is achieved by multi-view face detection in video frames, lip ROI extraction, color space transformation, vertical edge feature detection and lip localization by a feature-spatial profile analysis on a joint color-edge plane. One possible application of talking face detection in video is used to evaluate our work. Experimental results on TV programs and movies demonstrate that the proposed approach is efficient and robust in lip localization.

关键词： Face detection Skin Robustness TV Lips Laboratories Motion pictures Image quality Image segmentation Head

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Editorial: Knowledge engineering, semantics, and signal processing in audio - visual information retrieval

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IEEE Transactions on Circuits and systems for Video Technology 2007年第3期17卷 257-258页

作者： Izquierdo, Ebroul Zhang, Jian Sikora, Thomas Huang, Thomas S. Department of Electrical Engineering Queen Mary University of London London El 4NS United Kingdom Sydney Australia School of Computer Science and Engineering University of New South Wales Australia Communication Systems Group Technical University Berlin Berlin Germany ITG University of Illinois at Urbana-Champaign United States Department of Electrical and Computer Engineering Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Institute for Advanced Science and Technology United States Institute's Major Research Theme Human Computer Intelligent Interaction National Academy of Engineering Chinese Academies of Engineering and Sciences China International Association of Pattern Recognition Optical Society of American United States

No abstract available

关键词： Special issues and sections Knowledge engineering Information retrieval Audio-visual systems

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Perturbation Analysis for QR Factorization of Unitary-Symmetric Matrix

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电子学报(英文版) 2006年第3期15卷 455-459页

作者： ZOU Hongxing WANG Dianjun DAI Qionghai LI Yanda Department of Automation Tsinghua University Beijing 100084 China State Key Laboratory of Intelligent Technology and Systems Tsinghua University Beijing 100084 China National Laboratory of Pattern Recognition Institute of Automation The Chinese Academy of Sciences Beijing 100080 China Department of Mathematical Sciences Tsinghua University Beijing 100084 China

This paper considers the problem of perturbation analysis for the QR factorization of a special architecture called unitary-symmetric matrix. The perturbation bounds of the triangular factor and orthogonal factor in the QR factorization of unitary-symmetric matrix arc derived, together with the perturbation bound correspondences between the unitary-symmetric matrix and its mother matrix highlighted.

关键词： QR因数分解扰动分析对称矩阵正交因子

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Geometrical probability covering algorithm

Geometrical probability covering algorithm

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2nd International Conference on Fuzzy systems and Knowledge Discovery, FSKD 2005

作者： Zhang, Junping Li, Stan Z. Wang, Jue Shanghai Key Laboratory of Intelligent Information Processing Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences Beijing 100080 China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9783540283126

In this paper, we propose a novel classification algorithm, called geometrical probability covering (GPC) algorithm, to improve classification ability. On the basis of geometrical properties of data, the proposed algorithm first forms extended prototypes through computing means of any two prototypes in the same class. Then Gaussian kernel is employed for covering the geometrical structure of data and used as a local probability measurement. By computing the sum of the probabilities that a new sample to be classified to the set of prototypes and extended prototypes, the classified criterion based on the global probability measurement is achieved. The proposed GPC algorithm is simple but powerful, especially, when training samples are sparse and small size. Experiments on several databases show that the proposed algorithm is promising. Also, we explore other potential applications such as outlier removal with the proposed GPC algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Algorithms

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Adaptive nonlinear auto-associative modeling through manifold learning

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9th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, PAKDD 2005

作者： Zhang, Junping Li, Stan Z. Intelligent Information Processing Laboratory Department of Computer Science and Engineering Fudan University Shanghai 200433 China Key Laboratory of Complex Systems and Intelligence Science Chinese Academy of Sciences China National Laboratory of Pattern Recognition Center for Biometrics and Security Research Institute of Automation Beijing 100080 China

ISBN: (纸本)3540260765

We propose adaptive nonlinear auto-associative modeling (ANAM) based on Locally Linear Embedding algorithm (LLE) for learning intrinsic principal features of each concept separately and recognition thereby. Unlike traditional supervised manifold learning algorithm, the proposed ANAM algorithm has several advantages: 1) it implicitly embodies discriminant information because the suboptimal parameters of ANAM are determined based on error rate of the validation set. 2) it avoids the curse of dimensionality without loss accuracy because recognition is completed in the original space. Experiments on character and digit databases show that the advantages of the proposed ANAM algorithm. © Springer-Verlag Berlin Heidelberg 2005.

关键词： Learning systems

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Automatic evaluation of sentence fluency

Automatic evaluation of sentence fluency

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IEEE International Conference on systems, Man and Cybernetics

作者： Ding Liu Yu Zhou Chengqing Zong Fuji Ren National Laboratory of Pattern Recognition Institute of Automation Beijing China Department of Information Science and Intelligent Systems The University of Tokushima Japan

ISBN: (纸本)0780379527

In the machine translation (MT) system, how to evaluate the sentence fluency of the translation results is an important research topic. Most of the current methods are based on the similarity of output words compared with the reference translations, which don't specially address the evaluation of the sentence fluency according to the syntactic structure. This paper proposes a statistical approach to the problem, which is based on the n-gram language model and reference-independent. Our approach is a beneficial compensation to the reference-dependent methods and has better robustness than those methods based on the syntactic analysis. The preliminary experimental results indicate that the approach basically reflects the reality of human's judgment.

关键词： NIST Frequency Laboratories Automation Information science intelligent systems Machine intelligence Equations Humans Statistics

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Application of a genetic algorithm in triangulation of a 3-D object surface

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International Journal of Computers and Applications 2000年第2期22卷 73-77页

作者： Zhenyu, Chen Mbede, J.B. Yan, Zhou Dehua, Li Hanping, Hu State Commn. Res. Open Lab. Image P. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Intelligent Contr. and Robotics Lab. Dept. of Contr. Sci. and Engineering Huazhong Univ. of Sci. and Technol. 430074 Wuhan China Second Artillery Institute Huazhong Univ. of Sci. and Technol. Inst. Pattern Recog. Artif. Intell. Huazhong Univ. of Sci. and Technol. Second Artillery Institute China Wuhan University China Artificial Intelligence Department University of Edinburgh Inst. of AI and Pattern Recognition Huazhong Univ. of Sci. and Technol. China Cogn. Sci. Natl. Key Found. Res. P. Douala University Cameroon Tübingen University Germany Automatic Control Laboratory Darmstadt University Department of Service Cameroon Min. of National Education Robotics Laboratory Huazhong Univ. of Sci. and Technol. Wuhan China Assoc. Connectionnistes These-ACTH Rennes France IEEE Soc. of Robotics and Automation IEEE Society of Control Systems IASTED Assoc. Jeunes Chercheurs Robotique France Navy University of Engineering China Huazhong Univ. of Sci. and Technol. China Department of Computer Science Airforce Radar Acad. of Engineering China Inst. of P.R and AI Huazhong Univ. of Sci. and Technol.

This paper proposes a genetic-based algorithm for surface reconstruction of three-dimension (3-D) objects from a group of contours representing its section plane lines. The algorithm can optimize the triangulation of the surface of 3-D objects with a multi-objective optimization function to meet the needs of a wide range of applications. Further, a new crossover operator for triangulation and a new 3-D quadrilateral mutation operator are also introduced.

关键词： Object recognition

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