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检索条件"任意字段=7th Chinese Conference on Pattern Recognition and Computer Vision"

共 2194 条记录，以下是1311-1320 订阅

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7th chinese Semantic Web Symposium and the 2nd chinese Web Science conference, CSWS 2013

7th Chinese Semantic Web Symposium and the 2nd Chinese Web S...

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7th chinese Semantic Web Symposium and the 2nd chinese Web Scienceconference, CSWS 2013

ISBN: (纸本)9783642540240

the proceedings contain 23 papers. the special focus in this conference is on Linked Data and Knowledge Graph. the topics include: A new model to compute semantic similarity from multi-ontology;linked data platform D2R+;an ontology-based approach to extracting semantic relations from descriptive text;linking biomedical data for disease-SNP relation discovery;graph compression strategies for instance-focused semantic mining;searching semantic associations based on virtual document;a semantic web information integration system based on ontology-mapping and multilevel query interface;promoting integrated social and medical care through semantic integration and context visualization;a subject partitioning based SPARQL query engine and its NoSQL implementation;multi-criteria axiom ranking based on analytic hierarchy process;learning domain-specific ontologies from the web;effective chinese relation extraction by sentence rolling and candidate ranking;toward ontology representation and reasoning for news;approach for automatic construction of ontology based on medication guide;evaluating article quality and editor reputation in Wikipedia;ontology construction in tea pest domain and integration of pattern-based debugging approach into RaDON.

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Automatic Human Age Estimation Using Overlapped Age Groups 1

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7th International Joint conference on computer vision, Imaging and computer Graphics theory and Applications, VISIGRAPP 2012

作者： Kilinc, Merve Akgul, Yusuf Sinan TUBITAK - BILGEM 41470 Kocaeli Turkey GIT Vision Lab. Department of Computer Engineering Gebze Institute of Technology 41400 Kocaeli Turkey

ISBN: (数字)9783642382413

ISBN: (纸本)9783642382406

Facial aging effects can be perceived in two main forms;the first one is the growth related transformations and the second one is the textural variations. therefore, in order to generate an efficient age classifier, both shape and texture information should be used together. In this work, we present an age estimation system that uses the fusion of geometric features (ratios of distance values between facial landmark points) and textural features (filter responses of the face image pixel values). First the probabilities of a face image belonging to each overlapping age groups are calculated by a group of classifiers. then an interpolation based technique is used to produce the final estimated age. Many different textural features and geometric features were compared in this study. the results of the experiments show that the fusion with the geometric features increases the performance of the textural features and the highest age estimation rates are obtained using the fusion of Local Gabor Binary patterns and Geometric features with overlapping age groups. © Springer-Verlag Berlin Heidelberg 2013.

关键词： Local binary pattern

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Ordinal Random Forests for Object Detection 1

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35th German conference on pattern recognition (GCPR)

作者： Schulter, Samuel Roth, Peter M. Bischof, Horst Graz Univ Technol Inst Comp Graph & Vision A-8010 Graz Austria

ISBN: (数字)9783642406027

ISBN: (纸本)9783642406010;9783642406027

In this paper, we present a novel formulation of Random Forests, which introduces order statistics into the splitting functions of nodes. Order statistics, in general, neglect the absolute values of single feature dimensions and just consider the ordering of different feature dimensions. Recent works showed that such statistics have more discriminative power than just observing single feature dimensions. However, they were just used as a preprocessing step, transforming data into a higher dimensional feature space, or were limited to just consider two feature dimensions. In contrast, we integrate order statistics into the Random Forest framework, and thus avoid explicit mapping onto higher dimensional spaces. In this way, we can also exploit more than two feature dimensions, resulting in increased discriminative power. Moreover, we show that this idea can easily be extended for the popular Hough Forest framework. the experimental results demonstrate that using splitting functions building on order statistics can improve both, the performance for classification tasks (using Random Forests) and for object detection (using Hough Forests).

关键词： Object detection

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Object tracking across non-overlapping cameras using adaptive models

Object tracking across non-overlapping cameras using adaptiv...

引用

11th Asian conference on computer vision, ACCV 2012

作者： Chen, Xiaotang Huang, Kaiqi Tan, Tieniu National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences China

ISBN: (纸本)9783642374838

In this paper, we propose a novel approach to track multiple objects across non-overlapping cameras, which aims at giving each object a unique label during its appearance in the whole multi-camera system. We formulate the problem of the multiclass object recognition as a binary classification problem based on an AdaBoost classifier. As the illumination variance, viewpoint changes, and camera characteristic changes vary with camera pairs, appearance changes of objects across different camera pairs generally follow different patterns. Based on this fact, we use a categorical variable indicating the entry/exit cameras as a feature to deal with different patterns of appearance changes across cameras. For each labeled object, an adaptive model describing the intraclass similarity is computed and integrated into a sequence based matching framework, depending on which the final matching decisions are made. Multiple experiments are performed on different datasets. Experimental results demonstrate the effectiveness of the proposed method. © 2013 Springer-Verlag.

关键词： Object recognition

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Classification related manifold dimension estimation with restricted boltzmann machine

Classification related manifold dimension estimation with re...

引用

2013 7th International conference on Image and Graphics, ICIG 2013

作者： Teng, Kezhen Wang, Jinqiao National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769550503

To handle high dimensional variables in real world, especially multimedia data, dimension reduction techniques provide effective solutions for feature selection which makes the problem easy to deal in a lower dimension subspace. However, the primary problem with traditional dimension reduction method is to estimate intrinsic dimension of manifold supporting the raw data. Since all existing approaches of dimension reduction need to set the target dimension first. And for task of classification, the dimension we need maybe different from the intrinsic one, which means feature with intrinsic dimension may offer too much information for the classification task. In this paper, we propose a method to estimate classification related dimension with the help of RBM (Restricted Boltzmann Machine) and SVM classifiers. RBM is used for dimension reduction by mapping raw data to a low dimensional hidden space, and SVM classifier is used to test information preserving ability of this hidden space. An optimal dimension is selected as the minimum one that preserves all the classification related information of novel vectors. Further, a novel initialization strategy is proposed to speed up the training of RBM. these new methods are with low time consumption and memory cost compared to many other approaches of dimension estimation. Experiments and comparisons on several synthetic and realistic datasets show the superiority of the proposed method. © 2013 IEEE.

关键词： Classification (of information)

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Shape Analysis using the Spectral Graph Wavelet Transform

Shape Analysis using the Spectral Graph Wavelet Transform

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IEEE 9th International conference on e-Science (e-Science)

作者： Gomes Leandro, Jorge de Jesus Cesar, Roberto Marcondes, Jr. Feris, Rogerio Schmidt Univ Sao Paulo Inst Math & Stat Comp Sci Deparment Sao Paulo Brazil IBM Corp Thomas J Watson Res Ctr Yorktown Hts NY 10598 USA

ISBN: (纸本)9780769550831

the present work describes a framework for morphological characterization of galaxies based on the Spectral Graph Wavelet Transform. A galaxy image is sampled with a number of points randomly chosen, whose Delaunay triangulation results in an arbitrary graph. the average intensity value in a 5x5 vicinity of a pixel related to a graph vertex is assigned to the corresponding graph vertex. A weight inversely proportional to the photometric distance between each pair of vertices is assigned to the respective graph edge. the Spectral Graph Wavelet Transform is computed from this weighted graph with real-valued vertices yielding a high-dimensional feature vector, which is reduced to a two dimensional vector through Principal Component Analysis. the proposed framework has been assessed through two case studies, namely, the case study of analyzing (i) 2D binary images from shapes and preliminary results of (ii) 2D gray tone images from galaxies. the obtained results imply the suitability of this framework for the characterization of galaxies images.

关键词： computer vision graphs pattern recognition shape analysis spectral graph wavelet transform spectral graphs wavelets

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Towards a Secure Certificateless Proxy Re-Encryption Scheme 1

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7th International conference on Provable Security (ProvSec)

作者： Guo, Hui Zhang, Zhenfeng Zhang, Jiang Chen, Cheng Chinese Acad Sci Inst Software Trusted Comp & Informat Assurance Lab Beijing Peoples R China

ISBN: (数字)9783642412271

ISBN: (纸本)9783642412271;9783642412264

Proxy re-encryption (PRE) is an attractive paradigm, which gives good solutions to the problem of delegation of decryption rights. In proxy re-encryption, a semi-trusted proxy translates a ciphertext for Alice into a ciphertext of the same plaintext for Bob, without learning any information of the underlying message. As far as we know, previous PRE schemes are mainly in traditional public key infrastructure or identity-based cryptography, thus they suffer from certificate management problem or key escrow problem in practice. In order to solve these practical problems, we aim at constructing certificateless proxy re-encryption (CL-PRE) schemes. In this paper, we first introduce a security definition against (replayable) chosen ciphertext attack (CCA) for certificateless proxy re-encryption. In our security model, the adversary is allowed to adaptively corrupt users (in a specific pattern). then, we give some evidence that it is not easy to construct a secure CL-PRE. Actually, we present an attack to the chosen plaintext secure CL-PRE scheme proposed by Xu et al. [1]. We also show a novel generic construction for certificateless public key encryption (CL-PKE) can not be trivially adapted to CL-PRE by giving an attack to this generic construction. Finally, we present an efficient CL-PRE scheme and prove its security in the random oracle model based on well-known assumptions.

关键词： Public key cryptography

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Gender classification using faces and gaits

Gender classification using faces and gaits

引用

FTRA 7th International conference on Multimedia and Ubiquitous Engineering, MUE 2013

作者： Dang, Hong Quan Kim, Intaek Soh, Youngsung Department of Information and Communication Engineering Myongji University Yongin Korea Republic of

ISBN: (纸本)9789400767379

Gender classification is one of the challenging problems in computer vision. Many interactive applications need to exactly recognize human genders. In this paper, we are carrying out some experiments to classify the human gender in conditions of low captured video resolution. We use Local Binary pattern, Gray Level Co-occurrence Matrix to extract the features from faces and Gait Energy Motion, Gait Energy Image for gaits. We propose to combine face and gait features with the combination classifier to enhance gender classification performance. © 2013 Springer Science+Business Media Dordrecht(Outside the USA).

关键词： Local binary pattern

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Spatial graph for image classification

Spatial graph for image classification

引用

11th Asian conference on computer vision, ACCV 2012

作者： Wu, Zifeng Huang, Yongzhen Wang, Liang Tan, Tieniu National Lab. of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642373305

Spatial information in images is considered to be of great importance in the process of object recognition. Recent studies show that human's classification accuracy might drop dramatically if the spatial information of an image is removed. the original bag-of-words (BoW) model is actually a system simulating such a classification process with incomplete information. To handle the spatial information, spatial pyramid matching (SPM) was proposed, which has become the most widely used scheme in the purpose of spatial modeling. Given an image, SPM divides it into a series of spatial blocks on several levels and concatenates the representations obtained separately within all the blocks. SPM greatly improves the performance since it embeds spatial information into BoW. However, SPM ignores the relationships between the spatial blocks. To address this problems, we propose a new scheme based on a spatial graph, whose nodes correspond to the spatial blocks in SPM, and edges correspond to the relationships between the blocks. thorough experiments on several popular datasets verify the advantages of the proposed scheme. © 2013 Springer-Verlag.

关键词： Object recognition

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White Paper on Industrial Applications of computer vision and pattern recognition

White Paper on Industrial Applications of Computer Vision an...

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17th International conference on Image Analysis and Processing (ICIAP)

作者： Garibotto, Giovanni Murrieri, Pierpaolo Capra, Alessandro De Muro, Stefano Petillo, Ugo Flammini, Francesco Esposito, Mariana Pragliola, Concetta Di Leo, Giuseppe Lengu, Roald Mazzino, Nadia Paolillo, Alfredo D'Urso, Michele Vertucci, Raffaele Narducci, Fabio Ricciardi, Stefano Casanova, Andrea Fenu, Gianni De Mizio, Marco Savastano, Mario Di Capua, Michele Ferone, Alessio Selex ES Italy STMicroelectronics Catania Italy RFI Rete Ferroviaria Italiana Roma Italy Ansaldo STS Italy University of Naples Federico II Napoli Italy Dept. of Industrial Engineering University of Salerno Italy Biometric and Image Proc. Lab. University of Salerno Italy University of Cagliari Italy CIRA Italian Aerospace Research Centre Capua Italy CNR Napoli Italy Unlimited Software srl Naples Italy Dept. of Science and Technology University of Naples Parthenope Italy

ISBN: (纸本)9783642411847;9783642411830

the paper provides a summary of the contributions to the industrial session at ICIAP2013, describing a few practical applications of Video Analysis, in the Surveillance and Security field. the session has been organized to stimulate an open discussion within the scientific community of CVPR on new emerging research areas which deserve particular attention, and may contribute to the improvement of industrial applications in the near future.

关键词： computer vision

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