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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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Neural network algorithm for computing matrix eigenvalues and eigenvectors

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Ruan Jian Xue Bao/Journal of Software 2005年第6期16卷 1064-1072页

作者： Liu, Yi-Guang You, Zhi-Sheng Cao, Li-Ping Jiang, Xin-Rong Institute of Image and Graphics School of Computer Science and Engineering Sichuan University Chengdu 610064 China School of Public Administration Sichuan University Chengdu 610064 China

While using continuous time neural network described by the ***. learning rule (Oja-N) for computing real symmetrical matrix eigenvalues and eigenvectors, the initial vector must be on Rn unit hyper-sphere surface, otherwise, the network may produce limit-time overflow. In order to get over this defect, a new neural network (lyNN) algorithm is proposed. By using the analytic solution of the differential equation of lyNN, the following results are received: If initial vector belongs to a space corresponding to certain eigenvector, the lyNN equilibrium vector will converge in this space;If initial vector does not fall into the space corresponding to any eigenvector, the equilibrium vector will belong to the space spanned by eigenvectors corresponding to the maximum eigenvalue. The initial vector maximum space for the lyNN equilibrium vector will fall into space spanned by eigenvectors corresponding to any eigenvalue received. If the initial vector is perpendicular to a known eigenvector, so is the equilibrium vector. The equilibrium vector is on the hyper-sphere surface decided by the initial vector. By using the above results, a method for computing real symmetric matrix eigenvalues and eigenvectors using lyNN is proposed, the validity of this algorithm is exhibited by two examples, indicating that this algorithm does not bring about limit-time overflow. But for Oja-N, if the initial vector is outside the unit hyper-sphere and the matrix is negatively determinant, the neural network will consequentially produce limit-time overflow. Compared with other algorithms based on optimization, lyNN can be realized directly and its computing weight is lighter.

关键词： Neural networks

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Trigonometric polynomial B-spline with shape parameter

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自然科学进展(英文版) 2004年第11期14卷 1023-1026页

作者： Wang Wentao Wang Guozhao Institute of Computer Graphics and Image Department of Mathematics Zhejiang University Hangzhou 310027 China

The basis function of n order trigonometric polynomial B-spline with shape parameter is constructed by an integral approach. The shape of the constructed curve can be adjusted by changing the shape parameter and it ha... 详细信息

关键词： trigonometric polynomial B-spline with shape parameter basis function CAGD

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Multi lane line reconstruction for highway application with a signal view

Multi lane line reconstruction for highway application with ...

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Proceedings - Third International Conference on image and graphics

作者： Xin, Zhou Xi-yue, Huang Institute of Image and Graphics Dept. of Computer Sichuan University 610064 China Control and Navigation Laboratory Dept. of Automation Chongqing University 400044 China

ISBN: (纸本)0769522440

In the intelligent transportation systems, the automatic navigation system is the active research domain. The lane lines reconstruction based on the computer vision is the kernel technique. This paper describes the multi-lane line reconstruction with a single view for highway application. We calibrate the camera and get the model of the road. Then, detect the white lane lines and reconstruct the multi lane lines. This paper also analysis the basic way to keeping the road based on the vision model and the lane line model. We have experimented the system with the algorithms on highway at 150km/h in Sichuan province and Chongqing city in China. The result shows that the algorithms can work perfectly. © 2004 IEEE.

关键词： image reconstruction

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SAR and optical images fusion algorithm based on wavelet transform

SAR and optical images fusion algorithm based on wavelet tra...

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Proceedings of the Seventh International Conference on Information Fusion, FUSION 2004

作者： Wang, Yunfeng You, Zhisheng Wang, Jianguo Institute of Image and Graphics Computer Science College Sichuan University 610064 Chengdu Sichuan China EE Dept. Univ. Electron. Sci./Technol. China 610054 Chengdu Sichuan China

ISBN: (纸本)917056115X

Multisensor data fusion combines data and information from multiple sensors to achieve improved accuracies and better inference about the environment than single sensor alone. This paper presents a technique for fusing the Synthetic Aperture Radar (SAR) image and optical image at same scene using wavelet transform (WT) algorithm. Before fused the two images, a image registration affine transformation algorithm is presented at first, then selecting the maximized WT coefficient between SAR image and optical image, and inverse WT algorithm is executed using the selecting coefficient which described the typical target characters and presented the dominant information in their images. The results are given at last in figures formula and qualitative evaluation formula.

关键词： Synthetic aperture radar

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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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Multi lane line reconstruction for highway application with a signal view

Multi lane line reconstruction for highway application with ...

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International Conference on image and graphics (ICIG)

作者： Zhou Xin Huang Xi-yue Control and Navigation Laboratory Department of Automation Chongqing University China The Institute of Image and Graphics Department of Computer Sichuan University China

In the intelligent transportation systems, the automatic navigation system is the active research domain. The lane lines reconstruction based on the computer vision is the kernel technique. This paper describes the multi-lane line reconstruction with a single view for highway application. We calibrate the camera and get the model of the road. Then, we detect the white lane lines and reconstruct the multi lane lines. This paper also analysis the basic way in keeping the road based on the vision model and the lane line model. We have experimented the system with the algorithms on highway at 150 km/h in Sichuan province and Chongqing city in China. The result shows that the algorithms can work perfectly.

关键词： Road transportation image reconstruction Navigation Charge coupled devices Cameras Automated highways Application software Intelligent transportation systems Charge-coupled image sensors computer graphics

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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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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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