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International Conference on pattern recognition

作者： G. Langs P. Radeva D. Rotger F. Carreras Insitute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Vienna Austria Computer Vision Center Universitat Autònoma de Barcelona Bellaterra Spain Hospital St. Pau Barcelona Spain

In this paper, we address the problem of multimodal registration of coronary vessels by developing a 3D parametrical model of vessel trees from computer tomography data and registering it to angiography images during intervention. Thus, the interventionist takes profit from 3D data otherwise only available before the intervention. This facilitates orientation in ambiguous radiographs, interactive visualization of all vessel structures to estimate their mutual position and navigation within the vessel system and ultimately reduces the radiation the patient and the physicians are exposed to. The model is build by exploring the branching vessel tree starting from a single position and successively expanding through the vessels guided by a local deformable surface. The result is a tree of cylindrical segments each adapted to the vessel walls that is registered to angiography images in a fast and robust way. Validation on 8 patients confirms the robustness of our method.

关键词： X-ray imaging Computed tomography Robustness Angiography Image segmentation Image reconstruction Distortion measurement Tree graphs Data visualization Radio navigation

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A feasibility study of on-board data compression for infrared cameras of space observatories

A feasibility study of on-board data compression for infrare...

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International Conference on pattern recognition

作者： C. Reimers A.N. Belbachir H. Bischof R. Ottensamer D.A. Cesarsky H. Feuchtgruber F. Kerschbaum A. Poglitsch Institute of Astronomy University of Technology Vienna Vienna Austria Pattern Recognition and Image Procesing Group University of Technology Vienna Vienna Austria Institute of Computer Graphics and Vision Technical University of Graz Graz Austria Max-Planck Institute of Extraterrestrial Physics Garching Germany

In this paper, the feasibility of on-board data reduction/compression concept described in is evaluated for infrared images taken from space observatories. The method described in, which was initially designed and developed for the PACS (photodetector array camera and spectrometer) instrument, makes use of on-board integration to achieve higher compression ratio (CR) for applications with a modest telemetry rate. The evaluation of the reduction concept takes into account the visual performance (distortion) and the compression ratio. The distortion is assessed by calculating the reconstruction error using 4 metrics, namely, root mean square error (RMSE), signal-to-noise-ratio (SNR), peak-signal-to-noise-ratio (PSNR) and potential information loss (PIL). A quantitative evaluation of the on-board compression concept is performed on data from the infrared camera ISOCAM (infrared space observatory camera). We conclude with a short summary.

关键词： Data compression Cameras Observatories Image coding Infrared imaging Picture archiving and communication systems Photodetectors Spectroscopy Instruments Chromium

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On machine understanding of online handwritten mathematical expressions 7

On machine understanding of online handwritten mathematical ...

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7th International Conference on Document Analysis and recognition, ICDAR 2003

作者： Garain, Utpal Chaudhuri, B.B. Computer Vision and Pattern Recognition Unit Indian Statistical Institute 203 B. T. Road Kolkata India

ISBN: (纸本)0769519601

This paper aims at automatic recognition of online handwritten mathematical expressions written on an electronic tablet. The proposed technique involves two major stages: symbol recognition and structural analysis. A multiple-classifier consists of both parametric and nonparametric classifier has been used for recognition of symbols. Parametric classifier is based on Hidden Markov Model (HMM), whereas, non-parametric classifier uses Nearest Neighbor classification scheme. Structural analysis uses several online and offline features to identify the spatial relationships among symbols. A context free grammar has been designed to convert input expressions into their corresponding Latex strings. Contextual information has been used to correct several errors occurring at both recognition and structural analysis stage. A new method for evaluating performance of the proposed systems has been formulated. Experiments on a dataset of considerable size show high efficiency of the proposed system. © 2003 IEEE.

关键词： Structural analysis

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Preface

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2004年 3316卷 V-VI页

作者： Pal, Nikhil R. Kasabov, Nikola Mudi, Rajani K. Pal, Srimanta Parui, Swapan K. Indian Statistical Institute Electronics and Communications Sciences Unit 203 B. T. Road Calcutta India Private Bag 92006 Auckland New Zealand Jadavpur University Department of Instrumentation and Electronics Engineering Salt-lake Campus Calcutta India Indian Statistical Institute Computer Vision and Pattern Recognition Unit 203 B. T. Road Calcutta India

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Multi-script line identification from Indian documents

Multi-script line identification from Indian documents

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International Conference on Document Analysis and recognition

作者： U. Pal S. Sinha B.B. Chaudhuri Indian Statistical Institute Computer Vision and Pattern Recognition Unit Kolkata India

ISBN: (纸本)0769519601

A document page may contain two or more different scripts. For Optical Character recognition (OCR) of such a document page, it is necessary to separate different scripts before feeding them to their individual OCR system. In this paper an automatic scheme is presented to identify text lines of different Indian scripts from a document. For the separation task at first the scripts are grouped into a few classes according to script characteristics. Next feature based on water reservoir principle, contour tracing, profile etc. are employed to identify them without any expensive OCR-like algorithms. At present, the system has an overall accuracy of about 97.52%.

关键词： Natural languages Optical character recognition software computer vision pattern recognition Character recognition Water resources Reservoirs Constitution Writing Gabor filters

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recognition of printed Urdu script

Recognition of printed Urdu script

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International Conference on Document Analysis and recognition

作者： U. Pal A. Sarkar Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)0769519601

This paper deals with an Optical Character recognition system for printed Urdu, a popular Indian script. The development of OCR for this script is difficult because (i) a large number of characters have to be recognized (ii) there are many similar shaped characters. In the proposed system individual characters are recognized using a combination of topological, contour and water reservoir concept based features. The feature detection methods are simple and robust. A prototype of the system has been tested on printed Urdu characters and currently achieves 97.8% character level accuracy on average.

关键词： Reservoirs Water resources Optical character recognition software Character recognition Shape computer vision Image segmentation Water storage pattern recognition Robustness

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Segmentation of Bangla unconstrained handwritten text

Segmentation of Bangla unconstrained handwritten text

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International Conference on Document Analysis and recognition

作者： U. Pal S. Datta Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)0769519601

To take care of variability involved in the writing style of different individuals in this paper we propose a robust scheme to segment unconstrained handwritten Bangla texts into lines, words and characters. For line segmentation, at first, we divide the text into vertical stripes. Stripe width of a document is computed by statistical analysis of the text height in the document. Next we determine horizontal histogram of these stripes and the relationship of the minimal values of the histograms is used to segment text lines. Based on vertical projection profile lines are segmented into words. Segmentation of characters from handwritten word is very tricky as the characters are seldom vertically separable. We use a concept based on water reservoir principle for the purpose. Here we, at first, identify isolated and connected (touching) characters in a word. Next touching characters of the word are segmented based on the reservoir base area points and structural feature of the component.

关键词： Histograms Reservoirs Writing Robustness Statistical analysis Water resources computer vision pattern recognition Character recognition Handwriting recognition

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3-D human motion estimation using regularization with 2-D feature point tracking

3-D human motion estimation using regularization with 2-D fe...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Ya-Ming Wang Li Cao Wen-Qing Huang Research Center for Computer Vision and Pattern Recognition Zhejiang Institute of Science and Technology Hangzhou Zhejiang China

ISBN: (纸本)0780378652

A novel approach is proposed to 3-D human motion estimation using regularization. First, a method of feature point tracking is developed based on /spl alpha/-/spl beta/ filter and genetic algorithm. The outliers and occluded points can be solved by this method. Then, in order to deal with the ill-posed estimation problem, a regularization approach is proposed, which is based on the results of 2-D feature point tracking and the motion smoothness between consecutive estimation groups. Thus, the ill-posed problem is converted to a well-posed one. Experimental results also demonstrate the feasibility of the proposed approach.

关键词： Humans Motion estimation Tracking Filters Genetic algorithms computer vision Image sequences Biological system modeling Equations pattern recognition

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Classifiability based omnivariate decision trees

Classifiability based omnivariate decision trees

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International Joint Conference on Neural Networks (IJCNN)

作者： Y. Li M. Dong Machine Vision and Pattern Recognition Laboratory Department of Computer Science Wayne State University Detroit MI USA

Decision trees represent a simple and powerful method of induction from labeled examples. Univariate decision trees consider the value of a single attribute at each node, leading to the splits that are parallel to the axes. In linear multivariate decision trees, all the attributes are used and the partition at each node is based on a linear discriminate (a hyperplane). Nonlinear multivariate decision trees are able to divide the input space arbitrarily based on higher order parameterizations of the discriminate, though one should be aware of the increase of the complexity and the decrease in the number of examples available as moves further down the tree. In omnivariate decision trees, the decision node may be univariate, linear, or nonlinear. Such architecture frees the designer from choosing the appropriate tree type for a given problem. In this paper, we propose to do the model selection at each decision node based on a novel classifiability measure when building omnivariate decision trees. The classifiability measure captures the possible sources of misclassification with relative ease and is able to accurately reflect the complexity of subproblems at each node. The proposed approach does not require the time consuming statistic tests at each node and therefore does not suffer from as high computational burden as typical model selection algorithm. Our simulation results over several data sets indicate that our approach can achieve at least as good classification accuracy as statistical tests based model select algorithms, but in much faster speed.

关键词： Classification tree analysis Decision trees Testing Shape Machine vision pattern recognition Laboratories computer science Buildings Statistical analysis

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Communication via eye blinks and eyebrow raises: Video-based human-computer interfaces

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Universal Access in the Information Society 2003年第4期2卷 359-373页

作者： Grauman, K. Betke, M. Lombardi, J. Gips, J. Bradski, G.R. Vision Interface Group AI Laboratory Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Computer Science Department Boston University 111 Cummington St BostonMA02215 United States EagleEyes Computer Science Department Boston College Fulton Hall Chestnut HillMA02467 United States Vision Graphics and Pattern Recognition Microcomputer Research Laboratory Intel Corporation SC12-303 2200 Mission College Blvd Santa ClaraCA95054-1537 United States

Two video-based human-computer interaction tools are introduced that can activate a binary switch and issue a selection command. "BlinkLink," as the first tool is called, automatically detects a user's eye blinks and accurately measures their durations. The system is intended to provide an alternate input modality to allow people with severe disabilities to access a computer. Voluntary long blinks trigger mouse clicks, while involuntary short blinks are ignored. The system enables communication using "blink patterns:" sequences of long and short blinks which are interpreted as semiotic messages. The second tool, "EyebrowClicker," automatically detects when a user raises his or her eyebrows and then triggers a mouse click. Both systems can initialize themselves, track the eyes at frame rate, and recover in the event of errors. No special lighting is required. The systems have been tested with interactive games and a spelling program. Results demonstrate overall detection accuracy of 95.6% for BlinkLink and 89.0% for EyebrowClicker. © Springer-Verlag 2003.

关键词： computer vision

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