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IEEE International Conference on Networking, Sensing and Control

作者： Zhipeng Li Xiaobo Gong Yuncai Liu Institute of Image Processing Pattern Recognition Shanghai JiaoTong University Shanghai China Department of Control Science and Technology Shanghai JiaoTong University Shanghai China

This paper attempts to introduce a velocity-separation difference model that modifies the previous models in the literature. The improvement of this new model over the previous ones lies in that it performs more realistically than others in the dynamical evolution of congestion. Furthermore, the proposed model is investigated with analytic and numerical method, with the finding that this model can demonstrate some complex physical features observed in real traffic such as the existence of three phases: free flow, coexisting flow, and jam flow; sudden flow drop; traffic hysteresis in transition between the free and the coexisting flow

关键词： Testing Traffic control Telecommunication traffic Road vehicles Mathematical model Intelligent transportation systems Acceleration Hysteresis computer networks Computational modeling

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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

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

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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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Encoding Methods of Spectral Vector in Hyperspectral Romote Sensing image

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Journal of Shanghai University(English Edition) 2005年第1期9卷 52-57页

作者：杜培军方涛唐宏施鹏飞 Department of Remote Sensing and Geographical Information Science China University of Mining and Technology Xuzhou 221008 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 P.R. China

Taking into account the demands of hyperspectral remote sensing(RS) image retrieval and processing, some encoding methods of spectral vector including direct encoding, feature-based encoding and tree-based encoding methods are proposed and compared. In direct encoding, based on the analysis of binary encoding and quad-value encoding, decimal encoding is proposed. It is proved that quad-value encoding and decimal encoding are suitable to fast processing and retrieval. In absorption feature-based encoding method, five common metrics are compared. Because locations of reflection/absorption features are sensitive to noise, this method is not very effective in retrieval. In tree-based encoding methods, bitree, quadtree, octree and hextree are proposed and discussed. It is proved that 2-level octree and 2-level hextree are more effective than bitree and quadtree. Finally, quad-value encoding, decimal encoding, 2-level octree and 2-level hextree are proposed in spectral vectors encoding, similarity measure and hyperspectral RS image retrieval.

关键词： hyperspectral remote sensing spectral vector encoding similarity measure spectral angle.

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Multiple objects segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED)

Multiple objects segmentation based on maximum-likelihood es...

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International Conference on pattern recognition

作者： Xie Jun H.T. Tsui Xia Deshen Image Processing and Computer Vision Laboratory Department of Electronic Engineering Chinese University of Hong Kong Hong Kong China Pattern Recognition Laboratory Department of Computer Science Nanjing University of Science and Technology China

ISBN: (纸本)076951695X

A new method based on MLE-OED is proposed for unsupervised image segmentation of multiple objects which have fuzzy edges. It adjusts the parameters of a mixture of Gaussian distributions via minimizing a new loss function proposed to implement image segmentation based on the image's local spatial information and global intensity distribution properties. The loss function consists of two terms: a local content fitting term, which optimizes the entropy distribution, and a global statistical fitting term, which maximizes the likelihood of the parameters for the given data. The proposed segmentation method was validated by simulated and real examples. The performance in the experiments is better than those of two popular methods.

关键词： Object segmentation Maximum likelihood estimation image segmentation Layout Uncertainty image edge detection Shape measurement image processing pattern recognition Gaussian distribution

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Double-Row Cascade Labeling Algorithm for Hyper-Scale Issue

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Procedia Engineering 2011年 15卷 4047-4051页

作者： Yebin Fan Hualong Zhao Department of Computer Science Huazhong University of Science and Technology National Key Laboratory of Science and Technology on Multi-Spectral Information Processing Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology

An efficient algorithm is presented to label the connected components in the case that the primary memory is smaller than the image data. Our algorithm uses only the memory of two image rows to label the huge image or any image larger than the available memory. The search path compression is a applied for improving the performance further. An extensive comparison with the state-of-art algorithms is proposed, both on random and real datasets. Our algorithm shows an impressive speedup, while the auxiliary memory is not required at all comparing with all competitors.

关键词： Connected components labeling page fault hyper-scalar union-find

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Transmit power allocation for an extended V-BLAST system

Transmit power allocation for an extended V-BLAST system

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)

作者： Seung Hoon Nam Kwang Bok Lee Pattern Recognition and Image Processing Laboratory Samsung Advanced Institute of Science and Technology Suwon South Korea School of Electrical Engineering and Computer Science Seoul National University Seoul South Korea

ISBN: (纸本)0780375890

Vertical Bell Laboratories Layered Space-Time (V-BLAST) is a promising system that realizes the enormous capacity of multiple-input multiple-output (MIMO) communications. We present an extension of V-BLAST, and propose an effective transmit power allocation scheme for the extended system. The proposed transmit power allocation scheme minimizes the bit error rate (BER) averaged over all detection stages, and requires small feedback overhead from the receiver to the transmitter. Simulation results show that the extended V-BLAST system with the proposed transmit power allocation scheme provides a significant reduction in the BER compared to the conventional V-BLAST system. When the minimum mean square error (MMSE) nulling is adopted, the extended V-BLAST system is found to achieve the BER performance comparable to that of the maximum likelihood (ML) detection for the conventional V-BLAST architecture.

关键词： Bit error rate MIMO Feedback Transmitters Maximum likelihood detection Transmitting antennas Space technology computer science Mean square error methods Information theory

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Robust segmentation of freight containers in train monitoring videos

Robust segmentation of freight containers in train monitorin...

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IEEE Workshop on Applications of computer Vision (WACV)

作者： Qing-Jie Kong Avinash Kumar Narendra Ahuja Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

This paper is about a vision-based system that automatically monitors intermodal freight trains for the quality of how the loads (containers) are placed along the train. An accurate and robust algorithm to segment the foreground of containers in videos of the moving train is indispensable for this purpose. Given a video of a moving train consisting of containers of different types, this paper presents a method exploiting the information in both frequency and spatial domains to segment these containers. This method can accurately segment all types of containers under a variety of background conditions, e.g illumination variations and moving clouds, in the train videos shot by a fixed camera. The accuracy and robustness of the proposed method are substantiated through a large number of experiments on real data of train videos.

关键词： Robustness Freight containers Monitoring Videos image segmentation Rails Loading Clouds Cameras Lighting

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Analysis of appearance features for human matching between different fields of view

Analysis of appearance features for human matching between d...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaowei Lv Qing-Jie Kong Fei Weng Yuncai Liu Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Beckman Institute Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign Urbana IL USA

Human matching between different fields of view is a difficult problem in intelligent video surveillance; whereas fusing multiple features has become a strong tool to solve it. In order to guide the fusion scheme, it is necessary to evaluate the matching performance of these features. In this paper, four typical features are chosen for the evaluation. They are the color histogram, UV chromaticity, major color spectrum histogram, and scale-invariant features (SIFT). Quantities of video data are collected to test their general accuracy, robustness, and real-time applicability. The robustness is measured under the conditions of illumination changes, Gaussian and salt noises,foreground errors, resolution changes, and camera angle differences. The experimental results show that the four features bear distinctive performances under the different conditions, which will provide important references for the feature fusion methods.

关键词： Humans Colored noise Histograms Noise robustness Video surveillance Testing Noise measurement Lighting Gaussian noise Cameras

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Scatter correction algorithm without extra exposure for dual-energy digital mammography

Scatter correction algorithm without extra exposure for dual...

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Medical Imaging 2009: Physics of Medical Imaging

作者： Xi, Chen Xuanqin, Mou Hao, Yan Hengyong, Yu Lei, Zhang Institute of Image Processing and Pattern Recognition Xi'an Jiaotong University Xi'an Shaanxi 710049 China Biomedical Imaging Division School of Biomedical Engineering and Science Virginia Tech. Blacksburg VA 240601 United States Department of Computing Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong Hong Kong

ISBN: (纸本)9780819475091

X-ray scatter leads to erroneous calculations of dual-energy digital mammography (DEDM). The existing methods for scatter correction in DEDM are using anti-scatter grids or the pinhole-array interpolation method which is complicated and impractical. In this paper, a scatter correction algorithm for DEDM is developed based on the knowledge that scatter radiation in mammograms varies slowly and most pixels in mammograms are non-microcalcification pixels. The proposed algorithm only uses the information of low-energy (LE) and high-energy (HE) images. And it doesn't need anti-scatter grids, lead sheet and extra exposures. Our results show that the proposed scatter correction algorithm is effective. When using the simple least-squares fit and linear interpolation, the scatter to primary ratio (SPR) can be decreased from ~33.4% to ~2.8% for LE image and from ~26.2% to ~0.8% for HE image. Applying scatter correction to LE and HE images, the resultant background signal in the DE (dual-energy) calcification image an be reduced significantly. ©2009 SPIE.

关键词： Pixels

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