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检索条件"任意字段=MIPPR 2007: Pattern Recognition and Computer Vision"

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Internet der Dienste 1

引用

丛书名： acatech DISKUTIERT

1000年

作者： Lutz Heuser Wolfgang Wahlster

ISBN: (数字)9783642215070

Die Vereinfachung des Zugangs zu Informationen im Internet als Grundlagen für die Entwicklung neuer Dienstleistungen ist wesentliches Ziel des vom Bundesministerium für Wirtschaft und Technologie initiierten Forschungsprogramms THESEUS, welches von 2007 bis 2012 geplant ist. Am 14. September 2010 brachte acatech – Deutsche Akademie der Technikwissenschaften im Rahmen des Symposiums "Internet der Dienste" Experten aus Wissenschaft und Wirtschaft zusammen, die gemeinsam die Zwischenergebnisse des Forschungsprogramms sowie deren mögliche Umsetzung in innovative Anwendungen für den Standort Deutschland diskutierten. acatech möchte mit diesem Symposium deutlich machen, dass das Internet der Dienste und Dienstleistungen eine der zentralen Bestandteile des zukünftigen Internets sein wird.

关键词： computer Imaging, vision, pattern recognition and Graphics Communications Engineering, Networks

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Robust Histogram-Based Object Tracking in Image Sequences

Robust Histogram-Based Object Tracking in Image Sequences

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

作者： An Zhao HxI Initiative NICTA Eveleigh NSW Australia

ISBN: (纸本)9781424431618;9780769530673

Object tracking is an important aspect of computer vision which has attracted considerable attention recently. In this paper, we first introduce our framework for object tracking. Then, a new mathematical model for tracking performance analysis is presented. In addition, five matrix filters are designed and adopted to realize robust and efficient object tracking. Finally, an approach for combining histograms with different feature spaces into one histogram is given. According to our extensive experimental results, we found that our approaches greatly improve the visual tracking results.

关键词： Robustness Image sequences Histograms Target tracking computer vision Australia Layout Application software Performance analysis Filters

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A High-Performance Image Matching and recognition System for Multimedia Applications

A High-Performance Image Matching and Recognition System for...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Suya You Ulrich Neumann Integrated Media Systems Center Computer Science Department University of Southern California USA

This paper presents a high-performance image matching and recognition system for rapid and robust detection, matching and recognition of scene imagery and objects in varied backgrounds. Advanced image processing and pattern recognition technologies provide the system with object distinctiveness, robustness to occlusions, and invariance to scale and geometric distortions. Extensive experiments and several commercial applications have demonstrated the system's value and utility for multimedia applications.

关键词： Image matching Image recognition Multimedia systems Robustness Multimedia databases Image databases Layout Image retrieval computer vision Pixel

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Salient Coding for Image Classification

Salient Coding for Image Classification

引用

IEEE Conference on computer vision and pattern recognition

作者： Yongzhen Huang Kaiqi Huang Yinan Yu Tieniu Tan National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781457703942

The codebook based (bag-of-words) model is a widely applied model for image classification. We analyze recent coding strategies in this model, and find that saliency is the fundamental characteristic of coding. The saliency in coding means that if a visual code is much closer to a descriptor than other codes, it will obtain a very strong response. The salient representation under maximum pooling operation leads to the state-of-the-art performance on many databases and competitions. However, most current coding schemes do not recognize the role of salient representation, so that they may lead to large deviations in representing local descriptors. In this paper, we propose "salient coding", which employs the ratio between descriptors' nearest code and other codes to describe descriptors. This approach can guarantee salient representation without deviations. We study salient coding on two sets of image classification databases (15-Scenes and PASCAL VOC2007). The experimental results demonstrate that our approach outperforms all other coding methods in image classification.

关键词： Image classification Descriptors Codes Subject Headings coding

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Boosted Local Structured HOG-LBP for Object Localization

Boosted Local Structured HOG-LBP for Object Localization

引用

IEEE Conference on computer vision and pattern recognition

作者： Junge Zhang Kaiqi Huang Yinan Yu Tieniu Tan National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781457703942

Object localization is a challenging problem due to variations in object's structure and illumination. Although existing part based models have achieved impressive progress in the past several years, their improvement is still limited by low-level feature representation. Therefore, this paper mainly studies the description of object structure from both feature level and topology level. Following the bottom-up paradigm, we propose a boosted Local Structured HOGLBP based object detector. Firstly, at feature level, we propose Local Structured Descriptor to capture the object's local structure, and develop the descriptors from shape and texture information, respectively. Secondly, at topology level, we present a boosted feature selection and fusion scheme for part based object detector. All experiments are conducted on the challenging PASCAL VOC2007 datasets. Experimental results show that our method achieves the state-of-the-art performance.

关键词： Feature extraction Descriptors illumination Lighting topology Pascal based detector

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Variable Width Elliptic Gaussian Kernels for Probability Density Estimation

Variable Width Elliptic Gaussian Kernels for Probability Den...

引用

International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Service (TELSIKS)

作者： Dragoljub Pokrajac Longin Jan Latecki Aleksandar Lazarevic Jelena Nikolic Computer and Information Science Department Applied Mathematics Research Center and Center for Research and Education in Optical Sciences and Applications (CREOSA) Delaware State University Dover DE USA CIS Department Temple University Philadelphia PA USA CREOSA and United Technologies Research Center Hartford CT USA Faculty of Electronic Engineering University of Nis Nis Serbia

Estimation of probability density functions based on available data is important problem arising in various fields, such as telecommunications, machine learning, data mining, pattern recognition and computer vision. In this paper, we consider Kernel-based non-parametric density estimation methods and derive formulae for variable kernel density estimation using generalized, elliptic Gaussian kernels. The proposed technique is verified on simulated data.

关键词： Kernel Probability density function Machine learning Data mining pattern recognition computer vision Eigenvalues and eigenfunctions Random variables State estimation Optical computing

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A Discriminatively Trained, Multiscale, Deformable Part Model

A Discriminatively Trained, Multiscale, Deformable Part Mode...

引用

26th IEEE Conference on computer vision and pattern recognition (CVPR 2008), vol.7

作者： Pedro Felzenszwalb David McAllester Deva Ramanan University of Chicago USA Toyota Technological Institute Chicago USA University of California Irvine USA

This paper describes a discriminatively trained, multiscale, deformable part model for object detection. Our system achieves a two-fold improvement in average precision over the best performance in the 2006 PASCAL person detection challenge. It also outperforms the best results in the 2007 challenge in ten out of twenty categories. The system relies heavily on deformable parts. While deformable part models have become quite popular, their value had not been demonstrated on difficult benchmarks such as the PASCAL challenge. Our system also relies heavily on new methods for discriminative training. We combine a margin-sensitive approach for data mining hard negative examples with a formalism we call latent SVM. A latent SVM, like a hidden CRF, leads to a non-convex training problem. However, a latent SVM is semi-convex and the training problem becomes convex once latent information is specified for the positive examples. We believe that our training methods will eventually make possible the effective use of more latent information such as hierarchical (grammar) models and models involving latent three dimensional pose.

关键词： Deformable models Filters Support vector machines Object detection Data mining Spatial resolution Histograms computer vision Support vector machine classification Costs

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Pose Estimation Based on Two Images from Different Views

Pose Estimation Based on Two Images from Different Views

引用

IEEE Workshop on Applications of computer vision (WACV)

作者： Yuxing Mao Ching Y. Suen Caixin Sun Chunhua Feng The Key Laboratory of High Voltage Engineering & Electrical New Technology Ministry of Education Electrical Engineering College of Chongqing University Chongqing China Centre for Pattern Recognition and Machine Intelligence (CENPARMI) Concordia University Montreal QUE Canada

In this paper, we propose a new approach for face pose estimation based on two images from different views under certain conditions. Using a weak-perspective imaging model, six pose parameters were deduced, with four pairs of feature points properly chosen across the two face images. Through the scan-iteration algorithm, a robust performance was achieved, without solving non-linear equations. Comparing to some other methods which estimate rotation matrix based on fundamental matrix (F), our method focuses on the "absolute pose" with respect to front view rather than the "relative pose" between the two face images. "Absolute pose" is indispensable in most situations especially for 3D face modeling. Since our method does not depend on any 3D face models and frontal-view images, it can be applied not only to face recognition and 3D face modeling, but also to other relevant applications. Experimental results demonstrate the efficiency of our method

关键词： Face detection Head Video sequences Humans Robustness Face recognition Principal component analysis Feature extraction Application software pattern recognition

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Handwritten Bangla Compound Character recognition Using Gradient Feature

Handwritten Bangla Compound Character Recognition Using Grad...

引用

International Conference on Information Technology (ICIT)

作者： U. Pal T. Wakabayashi F. Kimura Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India Graduate School of Engineering Mie University Tsu Mie Japan

recognition of handwritten characters of Indian script is difficult because of the presence of many complex shaped compound characters (cluster characters) as well as variability involved in the writing style of different individuals. This paper deals with recognition of off-line Bangla handwritten compound characters using modified quadratic discriminant function (MQDF). The features used for recognition purpose are mainly based on directional information obtained from the arc tangent of the gradient. To get the feature, at first, a 2 times 2 mean filtering is applied 4 times on the gray level image and a non-linear size normalization is done on the image. A Roberts filter is then applied on the normalized image to obtain gradient image. Next, the arc tangent of the gradient (direction of gradient) is initially quantized into 32 directions and the strength of the gradient is accumulated with each of the quantized direction. Finally, the frequencies of these directions are down sampled using Gaussian filter to get 392 dimensional feature vectors. Using 5-fold cross validation technique we obtained 85.90% accuracy from a dataset of Bangla compound characters containing 20,543 samples.

关键词： Character recognition Handwriting recognition Filters pattern recognition Filtering Automation Information technology computer vision Writing Frequency

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Software and Data Technologies 1

引用

丛书名： Communications in computer and Information Science

1000年

作者： Joaquim Filipe Boris Shishkov Markus Helfert Leszek A. Maciaszek

ISBN: (数字)9783540886556

ISBN: (纸本)9783540886549

This book contains the best papers of the Second International Conference on So- ware and Data Technologies (ICSOFT 2007), held in Barcelona, Spain. It was org- ized by the Institute for Systems and Technologies of Information, Communication and Control (INSTICC), co-sponsored by the Workflow Management Coalition (WfMC), in cooperation with the Interdisciplinary Institute for Collaboration and Research on Enterprise Systems and Technology (IICREST). The purpose of ICSOFT 2007 was to bring together researchers and practitioners int- ested in information technology and software development. The conference tracks were “Software Engineering,” “Information Systems and Data Management,” “Programming Languages,” “Distributed and Parallel Systems” and “Knowledge Engineering.” Being crucial for the development of information systems, software and data te- nologies encompass a large number of research topics and applications: from imp- mentation-related issues to more abstract theoretical aspects of software engineering; from databases and data warehouses to management information systems and kno- edge-base systems; next to that, distributed systems, pervasive computing, data quality and other related topics are included in the scope of this conference.

关键词： Software Engineering/Programming and Operating Systems Programming Languages, Compilers, Interpreters Data Mining and Knowledge Discovery Software Engineering computer Imaging, vision, pattern recognition and Graphics Biometrics

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