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2005 16th British Machine Vision Conference, BMVC 2005

作者： Langs, Georg Peloschek, Philipp Donner, René Bischof, Horst Institute for Computer Graphics and Vision Graz University of Technology Austria Department of Diagnostic Radiology Medical University of Vienna Austria Pattern Recognition and Image Processing Group Vienna University of Technology Austria

ISBN: (纸本)1901725294

Autonomous model building is a crucial trend in model based methods like AAMs. This paper introduces an approach that deals with non-linearities by detecting distinct sub-parts in the data. Sub-models each representing an individual sub-part are derived from a minimum description length criterion. Thereby the resulting clique of models is more compact and obtains a better generalization behavior than a single model. The proposed AAM clique generation deals with non-linearities in the data in a generic information theoretic manner reducing the necessity of user interaction during training.

关键词： Information theory

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A robust matching algorithm for active appearance models 1

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Workshops Bildverarbeitung fur die Medizin: Algorithmen - Systeme - Anwendungen, BVM 2005 - Workshop on image processing for Medicine: Algorithms - Systems - Applications, BVM 2005

作者： Beichel, Reinhard Bischof, Horst Langs, Georg Sonka, Milan Institute for Computer Graphics and Vision Graz University of Technology Inffeldgasse 16/2 A-8010 Graz Austria Pattern Recognition and Image Processing Group Vienna University of Technology Favoritenstr. 9 A-1040 Vienna Austria Department of Electrical and Computer Engineering University of Iowa Iowa City IA 52242 United States

ISBN: (数字)9783540264316

ISBN: (纸本)3540250522

This paper proposes a method for robustly matching active appearance models (AAMs) on images with gross disturbances (outliers). The method consists of two steps. First, an initial residual is calculated by comparing model and image appearance, and modes of the residual are analyzed. Second, all possible mode combinations are tested by evaluating an objective function. The objective function allows the selection of an outlier-free mode combination. Experiments demonstrate the ability of the robust matching method to successfully cope with outliers - compared to standard AAM matching, no degeneration of the model during matching occurs.

关键词： Statistics

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Method for automatically segmenting the spinal cord and canal from 3D CT images

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11th International Conference on computer Analysis of images and Patterns, CAIP 2005

作者： Nyúl, Lászlo G. Kanyó, Judit Máté, Eörs Makay, Géza Balogh, Emese Fidrich, Márta Kuba, Attila Department of Image Processing and Computer Graphics University of Szeged Árpád tér 2 H-6720 Szeged Hungary Clinical Software Engineering GE Medical Systems Lajos u. 48-66 H-1036 Budapest Hungary Institute of Mathematics University of Szeged Aradi vértanuk tere 1 H-6720 Szeged Hungary

ISBN: (纸本)3540289690

We present two approaches for automatically segmenting the spinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to handle images where only part of the spinal column is visible. The algorithms require one seed point given on a slice located in the middle region of the spine, and the rest is automatic. The spatial extent of the spinal cord/canal is determined automatically. An extended region-growing technique is suggested for segmenting the spinal canal while active contours are applied if the spinal cord is to be segmented. Both methods work in 2D and use propagated information from neighboring slices. They are also very rapid in execution, that means an efficient, user-friendly workflow. The methods were evaluated by radiologists and were found to be useful (in reducing/eliminating contouring labor and time) and met the accuracy and repeatability requirements for the particular task. © Springer-Verlag Berlin Heidelberg 2005.

关键词： computerized tomography

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Knot modifications of B-spline or NURBS Surface

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of computer-Aided Design and computer graphics 2005年第5期17卷 986-989页

作者： Li, Yajuan Wang, Guozhao Department of Mathematics Institute of Computer Graphics and Image Processing Zhejiang University Hangzhou 310027 China

Modifying some knots of a B-spline or NURBS surface of order k×h to generate a family of B-spline or NURBS surface is presented. We show that the envelope of the family is a B-spline or NURBS surface defined by the same control points, and its order is (k-a)×(h-b), where a, b are the multiplicity of the modified knots. Moreover, any order partial derivatives of the B-spline surface and the family of B-spline surfaces differ only in a multiplier. The presented results can be served as a theoretical guidance for surface modeling and shape modifications in computer aided design today.

关键词： B-spline surface Envelope Knots modification NURBS surface Shape modifications

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Optimal sub-shape models by minimum description length

Optimal sub-shape models by minimum description length

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： G. Langs P. Peloschek H. Bischof Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Department of Clinical Radiology Vienna Medical University Vienna Austria

Active shape models are powerful and widely used tool to interpret complex image data. By building models of shape variation they enable search algorithms to use a priori knowledge in an efficient and gainful way. However, due to the linearity of PCA, non-linearities like rotations or independently moving sub-parts in the data can deteriorate the resulting model considerably. Although non-linear extensions of active shape models have been proposed and application specific solutions have been used, they still need a certain amount of user interaction during model building. In this paper the task of building/choosing optimal models is tackled in a more generic information theoretic fashion. In particular, we propose an algorithm based on the minimum description length principle to find an optimal subdivision of the data into sub-parts, each adequate for linear modeling. This results in an overall more compact model configuration. Which in turn leads to a better model in terms of modes of variations. The proposed method is evaluated on synthetic data, medical images and hand contours.

关键词： Active shape model Biomedical imaging Principal component analysis computer vision Linearity Polynomials Pattern recognition computer graphics Radiology image processing

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Object recognition using local information content

Object recognition using local information content

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International Conference on Pattern Recognition

作者： G. Fritz L. Paletta H. Bischof Joanneum Research Institute of Digital Image Processing Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

Object identification from local information has recently been investigated with respect to its potential for robust recognition, e.g., in case of partial object occlusions, scale variation, noise, and background clutter in detection tasks. This work contributes to this research by a thorough analysis of the discriminative power of local appearance patterns and by proposing to exploit local information content for object representation and recognition. In a first processing stage, we localize discriminative regions in the object views from a posterior entropy measure, and then derive object models from selected discriminative local patterns. Object recognition is then applied to test patterns with associated low entropy using an efficient voting process. The method is evaluated by various degrees of partial occlusion and Gaussian image noise, resulting in highly robust recognition even in the presence of severe occlusion effects.

关键词： Object recognition Noise robustness Entropy Background noise Object detection Information analysis Pattern analysis Pattern recognition Testing Voting

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Robust occupancy detection from stereo images

Robust occupancy detection from stereo images

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International Conference on Intelligent Transportation

作者： B. Alefs M. Clabian H. Bischof W. Kropatsch F. Khairallah Advanced Computer Vision GmbH-ACV Vienna Austria Advanced Computer Vision GmbH-ACV Austria Institute for Computer Graphics and Vision Graz University of Technology Graz Austria Pattern Recognition and Image Processing Group Institute of Computer Aided Automation Computer Science Department University of Technology Vienna Vienna Austria TRW Automotive GmbH Farmington Hills MI USA

Vehicle occupants that are out-of-position can be deadly injured by the deployment of the air bag in a crash situation. In recent years many different sensors and systems have been proposed to detect the type of occupant and the position of the occupant's head. This work presents a method for classification and occupant's head detection based on passive stereo vision. The proposed system uses depth surface analysis and scene statistics together with support vector machines for classification and selection of head candidates. Evaluation of the method shows 99% correct for classification and 98% correct for head detection, using large sets of image data, and image sequences recorded in a driving vehicle.

关键词： Robustness Magnetic heads Vehicle crash testing Sensor systems Stereo vision Layout Statistical analysis Support vector machines Support vector machine classification Vehicle detection

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Corrigendum to “Skeleton-driven 2D distance field metamorphosis using intrinsic shape parameters” [Graphical Models 66 (2004) 102–126]

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Graphical Models 2004年第4期66卷 261-261页

作者： WuJun Che XunNian Yang GuoZhao Wang Department of Mathematics Institute of Computer Graphics and Image Processing Zhejiang University Hangzhou 310027 PR China

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Uniform trigonometric polynomial B-spline curves

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Science in China(Series F) 2002年第5期45卷 335-343页

作者：吕勇刚汪国昭杨勋年 1. Institute of Computer Graphics and Image Processing Department of Mathematics Zhejiang University 310027 Hangzhou China

This paper presents a new kind of uniform spline curve, named trigonometric polynomial B-splines, over space Ω = span{sini,cost, tk-3,tk-4, …,t, 1} of which k is an arbitrary integer larger than or equal to 3. We show that trigonometric polynomial B-spline curves have many similar properties to traditional B-splines. Based on the explicit representation of the curve we have also presented the subdivision formulae for this new kind of curve. Since the new spline can include both polynomial curves and trigonometric curves as special cases without rational form, it can be used as an efficient new model for geometric design in the fields of CAD/CAM.

关键词： C-curves uniform B-splines C-B-splines trigonometric polynomial B-splines.

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Hierarchical top down enhancement of robust PCA 9th

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Joint IAPR 9th International Workshop on Structural and Syntactic Pattern Recognition, SSPR 2002 and 4th International Workshop on Statistical Techniques in Pattern Recognition, SPR 2002

作者： Langs, Georg Bischof, Horst Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Favoritenstr. 9 ViennaA-1040 Austria Institute for Computer Graphics and Vision TU Graz Inffeldgasse 16 2.OG GrazA-8010 Austria

ISBN: (纸本)3540440119

In this paper we deal with performance improvement of robust PCA algorithms by replacing regular subsampling of images by an irregular image pyramid adapted to the expected image content. The irregular pyramid is a structure built based on knowledge gained from the training set of images. It represents different regions of the image with different level of detail, depending on their importance for reconstruction. This strategy enables us to improve reconstruction results and therefore the recognition significantly. The training algorithm works on the data necessary to perform robust PCA and therefore requires no additional input. © Springer-Verlag Berlin Heidelberg 2002.

关键词： image enhancement

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