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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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APPROXIMATION MULTIDIMENSION FUCTION WITH FUNCTIONAL NETWORK

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Journal of Electronics(China) 2006年第1期23卷 81-84页

作者： Li Weibin Liu Fang Jiao Licheng Zhang Shuling Li Zongling Institute of Graphics and Image Processing Xianyang Normal University Xianyang 712000 China National Key Laboratory for Radar Signal Processing Xidian University Xi＇an 710071 China Insititute of Intelligent Information Processing Xidian University Xi＇an 710071 China

The functional network was introduced by ***, which extended the neural network. Not only can it solve the problems solved, but also it can formulate the ones that cannot be solved by traditional network. This paper applies functional network to approximate the multidimension function under the ridgelet theory. The method performs more stable and faster than the traditional neural network. The numerical examples demonstrate the performance.

关键词： Functional network Ridgelet Approximation

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Multi-step integer algorithm for non-unit voxel traversing along a 3D line

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Jisuanji Fuzhu Sheji Yu Tuxingxue Xuebao/Journal of Computer-Aided Design and Computer graphics 2006年第6期18卷 812-818页

作者： Liu, Yongkui Yun, Jian Wang, Xiaoqiang Song, Haiyu Institute of Computer Graphics and Image Processing Dalian Nationalities University Dalian 116600 China

An algorithm for traversing voxels along a 3D line using only integer arithmetic is presented. Two kinds of subdivision, namely non-unit space subdivision and non-square space subdivision, could be used. A 2D algorithm is first developed to find out the pixels a line passes through. Then based on it, an algorithm for traversing voxels along a 3D line in uniformly divided voxel space is proposed. Up to 3 voxels may be processed in one step and no accumulated error is made. The discriminator used in this algorithm is well refined, so that few calculations are required and the algorithm is simple and compact in form. Its comparison with existing voxel traversal algorithms shows that the new algorithm is not only free from accumulated error but also is the fastest.

关键词： 3D line generation Algorithm Traversal Voxel

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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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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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