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International Conference on Pattern Recognition

作者： M. Reiter R. Donner G. Langs H. Bischof Pattern Recognition and Image Processing Group Vienna University of Technology Austria Graz University of Technology Institute for Computer Graphics and Vision Austria

In this paper, we apply a multiple regression method based on canonical correlation analysis (CCA) to face data modelling. CCA is a factor analysis method which exploits the correlation between two high dimensional signals. We first use CCA to perform 3D face reconstruction and in a separate application we predict near-infrared (NIR) face texture. In both cases, the input data are color (RGB) face images. Experiments show, that due to the correlation between input and output signal, only a small number of canonical factors are needed to describe the functional relation of RGB images to the respective output (NIR images and 3D depth maps) with reasonable accuracy

关键词： Shape Face detection Lighting image reconstruction image analysis image databases Pattern analysis Rendering (computer graphics) image color analysis Pattern recognition

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Active Feature Models

Active Feature Models

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International Conference on Pattern Recognition

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

ISBN: (纸本)0769525210

In this paper active feature models are proposed. They utilize local texture features and a statistical shape model for the reliable localization of landmarks in images. They are related to active appearance models, but instead of modelling the entire texture of an object they represent image texture by means of local descriptors. The approach has advantages with complex image data like anatomical structures that exhibit high texture variation with limited relevance for the recognition of the object location. Experimental results and the comparison to AAMs on different data sets indicate that active feature models can improve search speed and result accuracy, considerably

关键词： Shape Active appearance model Biomedical imaging image texture image edge detection image texture analysis computer graphics Pattern recognition image processing Radiology

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Automatic Surveying of Cutaneous Hemangiomas

Automatic Surveying of Cutaneous Hemangiomas

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International Conference on Pattern Recognition

作者： S. Zambanini G. Langs R. Sablatnig P. Donath H. Maier Pattern Recognition and Image Processing Group University of Technology Vienna Austria Institute for Computer Graphics and Vision Graz University of Technology Austria Division of Special and Environmental Dermatologyy Medical University of Vienna Austria

This paper presents a method for the fully automatic surveying of cutaneous hemangiomas by means of a hemangioma segmentation and a ruler visible in the images. The algorithm computes the spatial resolution of an image. Hemangioma segmentation is accomplished by a single-layer perceptron classification by means of pixel color features. The algorithm was evaluated on a set of 120 images. It achieves satisfactory results on images with clearly visible, saturated hemangiomas

关键词： image segmentation Neoplasms Pattern recognition Spatial resolution Lesions Area measurement Pixel image processing computer graphics Biomedical imaging

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A clique of active appearance models by minimum description length

A clique of active appearance models by minimum description ...

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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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Novel vibro-acoustical technology for pipe deposition monitoring

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International Journal of COMADEM 2005年第4期8卷 24-32页

作者： Gelman, L. Jenkin, P. Petrunin, I. Sanderson, M. Thompson, C. Cranfield University National Technical University of Ukraine Cranfield University Department of Process and Systems Engineering Applied Mathematics and Computing Group Cranfield Beds MK43 0AL United Kingdom Applied Mathematics and Computing Group Cranfield University National Technical University of Ukraine KPI Department of Process and Systems Engineering Department of Fluid Instrumentation School of Engineering Cranfield University Centre for Computer Vision and Image Processing

Deposits (waxes, hydrates, etc.) change the damping properties of pipelines. The damping ratio of the pipeline increases with increments in deposit thickness. Thus, the evaluation of the damping ratio of the pipeline provides a condition monitoring of the pipeline deposits. Deposits could, be detected by monitoring the vibro-acoustical response of the pipeline while it is subjected to vibration excitation. Vibro-acoustical pipeline condition monitoring is a promising technology, but it has been little investigated. A novel vibro-acoustical technology of deposit detection in pipelines is proposed, developed, and validated through simulation. A new generic feature representation approach is used. Comparison of the proposed technology with the traditional technology based on the magnitude of the frequency response function is undertaken using simulation (by the Simulink) and Monte Carlo procedure. It is shown that the proposed technology provides an essential monitoring effectiveness gain vs. that of the technology based on the magnitude of the frequency response function. Thus, the proposed technology significantly improves the accuracy of vibro-acoustical deposit monitoring in pipelines. © 2005 COMADEM International.

关键词： Condition monitoring

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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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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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Detecting regional abnormal cardiac contraction in short-axis MR images using independent component analysis

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7th International Conference on Medical Imaging and computer Assisted Intervention, MICCAI 2004

作者： Suinesiaputra, A. Üzümcü, M. Frangi, A.F. Kaandorp, T. Reiber, J. Lelieveldt, B. Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Computer Vision Group Aragon Institute of Engineering University of Zaragoza Zaragoza Spain

ISBN: (纸本)3540229760

Regional myocardial motion analysis is used in clinical routine to inspect cardiac contraction in myocardial diseases such as infarction or hypertrophy. Physicians/radiologists can recognize abnormal cardiac motion because they have knowledge about normal heart contraction. This paper explores the potential of Independent Component Analysis (ICA) to extract local myocardial contractility patterns and to use them for the automatic detection of regional abnormalities. A qualitative evaluation was performed using 42 healthy volunteers to train the ICA model and 6 infarct patients to test the detection and localization. This experiment shows that the evaluation results correlate very well to the clinical gold standard: delayed-enhancement MR images. © Springer-Verlag Berlin Heidelberg 2004.

关键词： Independent component analysis

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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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Building and registering parameterized 3D models of vessel trees for visualization during intervention

Building and registering parameterized 3D models of vessel t...

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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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