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作者： Shen, Hongbin Yang, Jie Chen, Ningjiang Dong, Yifei Wang, Shitong Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 China Philips Research East Asia Shanghai 200070 China School of Computer Science and Engineering University of New South Wales Australia Department of Information Science Southern Yangtze University Wuxi Jiangsu 214036 China

Conventional clustering algorithms are designed for a single independent dataset, i.e. Fuzzy C-Means (FCM) clustering algorithm. In the real world, a dataset is independent of other datasets but sometimes can be cooperative with others by exchanging information, such as the relationship between subsidiary companies. We should therefore consider the influence from other relative collaborative datasets while performing clustering learning under such collaborative circumstances. In this paper, three different collaborative models are discussed and new correct methods are proposed to quantitatively measure such collaboration between datasets, i.e. information gain. The corresponding collaborative clustering algorithms are presented accordingly and the theoretical analysis shows that the new cooperative clustering algorithms can finally converge to a local minimum. Experimental results demonstrate that the clustering structures obtained by new cooperative algorithms are different from those of conventional algorithms for the consideration of collaboration and the performances of these collaborative clustering algorithms can be much better than those conventional single clustering algorithms under the cooperating circumstances. ©?2005-IOS Press and the authors. All rights reserved.

关键词： Clustering algorithms

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On the detection of individuals and vehicles on an airport's apron

On the detection of individuals and vehicles on an airport's...

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IEE International Conference on Visual Information Engineering (VIE 2005)

作者： Josep Aguilera Antequera Martin Kampel Vienna University of Technology Institute of Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr.9 183-2 A-1 040 Vienna Austria

This paper gives a robust motion detection and tracking solution for a video surveillance application on an airport's apron. As an outdoor application, the system must be capable of adapting to a wide range of weather conditions and illumination changes, furthermore, the achromaticity of the scene and the presence of occlusions in the tracking process are issues considered in the selection of the motion detector and tracking system respectively. We propose an adapted mixture of Gaussiani model with RGB colour normalisation to detect mobile objects in the scene and a region tracking method based on significant mobile object features to track individuals and vehicles on the selected airport's apron. The performance of the proposed motion detector is evaluated using pixel-based performance metrics and compared with other existing methods. The capability of the application to handle partial occlusions is tested on the region tracker.

关键词： Tracking Airports Surveillance Adaptation models Visualization Motion detection Atmospheric modeling

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Visual Surveillance for Aircraft Activity Monitoring

Visual Surveillance for Aircraft Activity Monitoring

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Joint IEEE International Workshop on Visual Surveillance and Performance Evaluation of Tracking and Surveillance

作者： D. Thirde M. Borg J. Ferryman V. Valentin F. Fusier F. Bremond M. Thonnat J. Aguilera M. Kampel Computational Vision Group University of Reading UK ORION Team I.N.R.I.A. Sophia Antipolis France Pattern Recognition and Image Processing Group University of Technology Vienna Austria

This paper presents a visual surveillance system for the automatic scene interpretation of airport aprons. The system comprises two modules - scene tracking and scene understanding. The scene tracking module, comprising a bottom-up methodology, and the scene understanding module, comprising a video event representation and recognition scheme, have been demonstrated to be a valid approach for apron monitoring

关键词： Surveillance Aircraft Monitoring Layout Tracking Motion detection Airports Vehicles image motion analysis Computer vision

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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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Using string kernel to predict signal peptide cleavage site based on subsite coupling model (vol 28, pg 395, 2005)

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AMINO ACIDS 2005年第3期29卷 301-301页

作者： Wang, M Yang, J Chou, KC Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Microsoft Research Asia Beijing China Institute of Bioinformatics and Drug Discovery Tianjin China Gordon Life Science Institute San Diego U.S.A.

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Microscopic Halftone image Segmentation

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Journal of Donghua University(English Edition) 2004年第5期21卷 83-87页

作者：王永刚杨杰丁永生 Institute of Image Processing & pattern Recognition Shanghai Jiaotong University Shanghai 200030 Dr Institute of Image Processing & pattern Recognition Shanghai Jiaotong University Shanghai 200030 College of Information Science and Technology Donghua University Shanghai 200051 Digitized Textile & Fashion Technology Engineering Research Center of National Education Ministry Donghua University Shanghai 200051

Microscopic halftone image recognition and analysis can provide quantitative evidence for printing quality control and fault diagnosis of printing devices, while halftone image segmentation is one of the significant steps during the procedure. Automatic segmentation on microscopic dots by the aid of the Fuzzy C-Means (FCM) method that takes account of the fuzziness of halftone image and utilizes its color information adequately is realized. Then some examples show the technique effective and simple with better performance of noise immunity than some usual methods. In addition, the segmentation results obtained by the FCM in different color spaces are compared, which indicates that the method using the FCM in the f 1f 2f 3 color space is superior to the rest.

关键词： image segmentation color halftone printing FCM color space

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The morphological top-hat operator generalised to multi-channel images

The morphological top-hat operator generalised to multi-chan...

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International Conference on pattern recognition

作者： A. Hanbury Pattern Recognition and Image Processing Group (PRIP) University of Technology Vienna Vienna Austria

The morphological top-hat operator for grayscale images is part of the basic toolbox of mathematical morphology operators. We discuss two ways of generalising the top-hat operator to multi-channel images, such as colour images. The first method presented is the use of a vectorial order in the relevant vector space. The second is based on the demonstration that the top-hat operator can be rewritten in terms of increments. These increments can be replaced by any vectorial distance function, removing the requirement to first impose an order on the vectors. We present examples of the use of the suggested top-hat operators in feature detection in colour images and defect detection in texture.

关键词： Morphology Data mining pattern recognition image processing Computer vision Object detection Muscles image color analysis image texture analysis

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On 3D mosaicing of rotationally symmetric ceramic fragments

On 3D mosaicing of rotationally symmetric ceramic fragments

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International Conference on pattern recognition

作者： M. Kampel R. Sablatnig Institute of Computer Aided Automation Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

A major obstacle to the wider use of 3D object reconstruction and modeling is the extent of manual intervention needed. Such interventions are currently massive and exist throughout every phase of a 3D reconstruction project: collection of images, image management, establishment of sensor position and image orientation, extracting the geometric detail describing an object, merging geometric, texture and semantic data. This work aims to develop a solution for automated documentation of archaeological pottery, which also leads to a more complete 3D model out of multiple fragments. Generally the 3D reconstruction of arbitrary objects from their fragments can be regarded as a 3D puzzle. In order to solve it we identified the following main tasks: 3D data acquisition, orientation of the object, classification of the object and reconstruction. We demonstrate the method and give results on synthetic and real data.

关键词： Ceramics image reconstruction pattern recognition Assembly Surface cracks Surface reconstruction Automation image processing Manuals Project management

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A novel video object tracking approach using bidirectional projection

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Chinese Optics Letters 2004年第7期2卷 390-392页

作者：刘志杨杰 Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030 Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai 200030his paper proposes a novel video object tracking approach using birdirectional projection. Forward projection is exploited to locate the current video object with rough boundary information. Watershed segmentation is applied to the simplified gradient image of the current frame to obtain a reasonable partition. An improved backward projection which incorporates pixel classification with region classification is performed on some segmented regions in a rather small search range and the tracking performance is enhanced in respect to both reliability and efficiency. Experimental results for various types of the MPEG-4 (moving picture experts group) test sequences demonstrate an efficient and faithful segmentation performance of the proposed approach.

This paper proposes a novel video object tracking approach using birdirectional projection. Forward projection is exploited to locate the current video object with rough boundary information. Watershed segmentation is applied to the simplified gradient image of the current frame to obtain a reasonable partition. An improved backward projection, which incorporates pixel classification with region classification, is performed on some segmented regions in a rather small search range, and the tracking performance is enhanced in respect to both reliability and efficiency. Experimental results for various types of the MPEG-4 (moving picture experts group) test sequences demonstrate an efficient and faithful segmentation performance of the proposed approach.

关键词： Segmentation Video

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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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