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2010 International Conference on Computer Application and system Modeling, ICCASM 2010

作者： Wang, Rongyan Liu, Gang Guo, Jun Ma, Zhenxin Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9781424472369

Most previous approaches to automatic audio events (AEs) annotation are based on supervised learning which relies on the availability of a labeled corpus to train classification models. However, instance annotation is often difficult, expensive, and time consuming. In this paper, we apply semi- supervised learning with transductive Support Vector Machine (TSVM) algorithm to automatic AEs annotation. Besides, considering about the presence of outliers which degrade the generalization and the classification performance, we propose a confidence-based method for samples selection. In our experiments based on the melodrama Friends corpus, the proposed method can effectively use unlabeled data to improve the classification performance with only a small amount of the labeled data.

关键词： Supervised learning

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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电子学报(英文版) 2010年第3期19卷 451-456页

作者： LI Bo LIU Wenju DOU Lihua School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词：高斯混合模型图像分割无监督学习应用概率密度函数椭球等高分布模型估计高斯密度

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Matching image with multiple local features

Matching image with multiple local features

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International Conference on pattern recognition

作者： Cao, Yudong Zhang, Honggang Gao, Yanyan Xu, Xiaojun Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China Liaoning University of Technology Jinzhou China

ISBN: (纸本)9780769541099

In this paper, we present the fusional feature composed of Affine-SIFT, MSER and color moment invariants. The fusional feature is more robust and distinctive than a single local feature. Instead of adding three local features together simply, an efficient two-level matching strategy is devised with the fusional feature, which speeds up the establishment of the local correspondences. To remove partial false positives, an affine transformation is estimated with the weighted RANSAC which decreases iteration times. The experimental results show that our approach can achieve more accurate correspondence. We prospect to apply the fusional feature and match strategy to image retrieval in the end. © 2010 IEEE.

关键词： Image matching

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AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFINE-SIFT FEATURE

AN EFFICIENT DUPLICATE IMAGE DETECTION METHOD BASED ON AFFIN...

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2010 3rd IEEE International Conference on Broadband Network & Multimedia Technology(2010年第三届IEEE宽带网络与多媒体国际会议 IC-BNMT 2010)

作者： Yudong Cao Honggang Zhang Yanyan Gao Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunica

In this paper, we present a novel scheme to tackle the task of near-duplicate image detection. Given two input images, the algorithm based on the refined similarity measure can judge rightly whether two input image are duplicate images or not. The two images are represented with local feature (i.e, Affine-SIFT) in bag of features model. The Affine-SIFT can undergo larger affine distortions than Hessian-Affine and MSER (Maximally Stable Extremal Region). The refined similarity measure exploits the spatial information between two images. The algorithm is demonstrated on some image pairs with scale change, viewpoint change, blur, noise and spatial deformation. The experimental results show that proposed algorithm is more effective than other state-of-the-art duplicate image detection algorithm.

关键词： duplicate detection image matching Affine-SIFT

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NOVEL ACTIVE LEARNING SAMPLE EVALUATION METHOD BASED ON MULTI-LEVEL CONFUSION NETWORKS

NOVEL ACTIVE LEARNING SAMPLE EVALUATION METHOD BASED ON MULT...

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Wei Chen Jun Guo Gang Liu Pattern Recognition and Intelligent System LaboratoryBeijing University of Posts and Telecommunicati Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunicat

Active Learning (AL) is designed to aid the laborintensive process of training acoustic model for speech recognition. In AL, only the most informative training samples are selected for manual annotation. Thus, how to evaluate the unlabeled samples is worth researching. In this paper, we propose a unified framework to generate confusion networks of multiple levels including character, syllable and phone, and present a novel active learning sample evaluation method for Chinese acoustic modeling, posterior probabilities obtained from multi-level confusion networks are respectively adopted to evaluate the unlabeled samples. Our experiments show that compared with the widely used sample evaluation method using word posterior probability obtained from word confusion network, our proposed method can achieve satisfying performances.

关键词： Active learning confusion network acoustic model speech recognition

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An efficient duplicate image detection method based on Affine-SIFT feature

An efficient duplicate image detection method based on Affin...

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2010 3rd IEEE International Conference on Broadband Network and Multimedia Technology, IC-BNMT2010

作者： Cao, Yudong Zhang, Honggang Gao, Yanyan Guo, Jun Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China College of Electrical and Information Engineering Liaoning University of Technology Jinzhou China

ISBN: (纸本)9781424467709

关键词： Affine-SIFT Duplicate detection Image matching

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BLOG EXTRACTION WITH TEMPLATEINDEPENDENT WRAPPER

BLOG EXTRACTION WITH TEMPLATEINDEPENDENT WRAPPER

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2010 2nd IEEE International Conference on Network Infrasturcture & Digital Content(2010年第二届IEEE网络基础设施与数字内容国际会议 IC-NIDC 2010)

作者： Zhixuan Zhang Chuang Zhang Zhiqing Lin Bo Xiao Pattern Recognition and Intelligent System Laboratory(PRIS) Beijing University of Posts and Telecomm Pattern Recognition and Intelligent System Laboratory(PRIS) Beijing University of Posts and Telecom

Rich information is contributed to blogs by millions of users all around the world with the development of blogsphere. However, few work has been done on the study of blog extraction so far. Unlike the traditional template-dependent wrapper, not only blog articles but also blogroll is extracted with template-independent wrapper in this paper. In our method, blog extraction is formalized as a machine learning problem and a template-independent wrapper is learned by using labeled blog pages from a single site. Testing pages are obtained from 10 popular Chinese blog sites. And experimental results on 300 real blog pages indicate that the proposed method can correctly extract data from blogs with the accuracy of 90％ or even above.

关键词： template-independent data extraction web mining

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Automatic face replacement in video based on 2D morphable model

Automatic face replacement in video based on 2D morphable mo...

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International Conference on pattern recognition

作者： Min, Feng Sang, Nong Wang, Zhefu Hubei Key Laboratory of Intelligent Robot Wuhan Institute of Technology Wuhan China Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9780769541099

This paper presents an automatic face replacement approach in video based on 2D morphable model. Our approach includes three main modules: face alignment, face morph, and face fusion. Given a source image and target video, the Active Shape Models (ASM) is adopted to source image and target frames for face alignment. Then the source face shape is warped to match the target face shape by a 2D morphable model. The color and lighting of source face are adjusted to keep consistent with those of target face, and seamlessly blended in the target face. Our approach is fully automatic without user interference, and generates natural and realistic results. © 2010 IEEE.

关键词： 2D morphable model active shape models automatic face replacement face alignment face fusion face morph face recognition image morphing shape recognition source face shape video signal processing

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An accurately located method and secure scheme for image authentication

An accurately located method and secure scheme for image aut...

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International Conference on Multimedia Technology

作者： Wang, Zuxi Wang, Wenzong Dong, Liefeng Ye, Peng Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control Wuhan China Ningbo Polytechnic Ningbo China

ISBN: (纸本)9781424478743

A novel authentication watermarking scheme for images is proposed in this paper, which holds accuracy location and high security at the same time. In the scheme, different keys are selected for different host data, and the generation and insertion of watermark is dependent on the selected key. Analyzing different pieces of watermarked data in order to launch an attack becomes impossible because of the lack of common characteristics in these pieces. Beside, to increase the security of system, the chaos technology is used to encrypt the watermark and shuffle the location of embedding. A method for tamper detecting based on the running window is proposed in the scheme. Not only can it distinguish malicious attacks from unintentional attacks, but also it can locate the tampered area accurately. Experimental results show this semi-fragile watermarking algorithm is effective and practical for content authentication. ©2010 IEEE.

关键词： Authentication

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Cross-Document Coreference Resolution Based on Automatic Text Summary

Cross-Document Coreference Resolution Based on Automatic Tex...

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International Workshop on Knowledge Discovery and Data Mining (WKDD)

作者： Sanyuan Gao Si Li Weiran Xu Jun Guo Pattern Recognition and Intelligent System Laboratory Beijing University of Posts and Telecommunications Beijing China

ISBN: (纸本)9781424453979

Cross-document coreference resolution plays an import part in the filed of natural language processing (NLP). It captures the ability of gathering documents for information about a certain entity. Most previous algorithms identify the underlying entity of a given document depending on the original text, which is unreliable if the original text contains multiple parts of different themes. In this paper, we propose a cross-document coreference resolution algorithm based on automatic text summary instead of the original text. In our approach, we extract query-specific and informative-indicative summary from the original text by using Hobbs algorithm and measure the similarity between two summaries. This automatic text summary-based cross-document coreference resolution (ATSCDCR) system is effective in disambiguating different entities of the same mention name and identifying the same entity of different mention names. The results from our experiments show that the macro average of ATSCDCR system is up to 73.16% and the micro average of ATSCDCR system is 67.34 %.

关键词： Data mining Joining processes pattern recognition intelligent systems Electronic mail Natural language processing Text recognition Testing Biomedical informatics Displays

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