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Terrain Simplification Research in Augmented Scene Modeling

Journal of China University of Geosciences 2001年第4期12卷 351-355页

作者： Ming Delie You Kefei Tian Jinwen Liu Jian State Key Laboratory for image processing and Intelligent Control, Institute for pattern recognition and Artificial Intelligence , Huazhong University of Science and Technology , Wuhan 430074 Wang Guangju State Key Laboratory for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 Faculty of Information Engineering China University of Geosciences Wuhan 430074

Augmented reality is the merging of synthetic sensory information into a user's perception of a real environment. As one of the most important tasks in augmented scene modeling, terrain simplification research has gained more and more attention. In this paper, we mainly focus on point selection problem in terrain simplification using triangulated irregular network. Based on the analysis and comparison of traditional importance measures for each input point, we put forward a new importance measure based on local entropy. The results demonstrate that the local entropy criterion has a better performance than any traditional methods. In addition, it can effectively conquer the 'short-sight' problem associated with the traditional methods.

关键词： augmented reality scene modeling terrain simplification triangulated irregular network importance measures local entropy.

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A new approach of color quantization of image based on neural network

A new approach of color quantization of image based on neura...

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International Joint Conference on Neural Networks (IJCNN)

作者： Yingqian Wu Cuiping Yang Tianzhen Wang Institute of Image processing and Pattern recognition Shanghai Jiaotong University Shanghai China Institute of Image processing Wuhan University of Science and Technology Wuhan China

ISBN: (纸本)0780370449

In the paper, a new algorithm using a competitive Hopfield neural network for color quantization is proposed, and it completes two tasks of color palette design and pixels color mapping based on the pixel color value distribution. Results of the experiment show that the approach has the advantages of fast convergent speed and high quantization.

关键词： Neural networks Color Hopfield neural networks Quantization Pixel image processing image converters pattern recognition Paper technology Algorithm design and analysis

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3D modeling of archaeological vessels using shape from silhouette

3D modeling of archaeological vessels using shape from silho...

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International Conference on 3D Imaging, Modeling, processing, Visualization and Transmission (3DIMPVT)

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

ISBN: (纸本)0769509843

An algorithm for the automatic construction of a 3D model of archaeological vessels is presented. In archeology the determination of the exact volume of arbitrary vessels is of importance since this provides information about the manufacturer and the usage of the vessel. To acquire the shape of objects with handles in 3d is complicated, since occlusions of the object's surface are introduced by the handle and can only be resolved by taking multiple views. Therefore, the 3d reconstruction is based on a sequence of images of the object taken from different viewpoints. The object's silhouette is the only feature which is extracted from an input image. images are acquired by rotating the object on a turntable in front of a stationary camera. The algorithm uses an octree representation of the model, and builds this model incrementally, by performing limited processing of all input images for each level of the octree. Beginning from the root node at the level 0 a rough model of the object is obtained quickly and is refined as the processed level of the octree increases. Results of the algorithm developed are presented for both synthetic and real input images.

关键词： Shape Cameras Automation pattern recognition image processing Manufacturing image reconstruction Feature extraction Ceramics Distortion measurement

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Reconstruction of specular surfaces using polarization imaging

Reconstruction of specular surfaces using polarization imagi...

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Conference on Computer Vision and pattern recognition (CVPR)

作者： S. Rahmann N. Canterakis Institute for Pattern Recognition and Image Processing Computer Science Department University of Freiburg Freiburg im Breisgau Germany

ISBN: (纸本)0769512720

Traditional intensity imaging does not offer a general approach for the perception of textureless and specular reflecting surfaces. Intensity based methods for shape reconstruction of specular surfaces rely on virtual (i.e. mirrored) features moving over the surface under viewer motion. We present a novel method based on polarization imaging for shape recovery of specular surfaces. This method overcomes the limitations of the intensity based approach because no virtual features are required. It recovers whole surface patches and not only single curves on the surface. The presented solution is general as it is independent of the illumination. The polarization image encodes the projection of the surface normals onto the image and therefore provides constraints on the surface geometry. Taking polarization images from multiple views produces enough constraints to infer the complete surface shape. The reconstruction problem is solved by an optimization scheme where the surface geometry is modelled by a set of hierarchical basis functions. The optimization algorithm proves to be well converging, accurate and noise resistant. The work is substantiated by experiments on synthetic and real data.

关键词： image reconstruction Surface reconstruction Polarization Shape Geometry Surface texture Lighting Solid modeling image converters Multi-stage noise shaping

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Illumination insensitive eigenspaces

Illumination insensitive eigenspaces

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International Conference on Computer Vision (ICCV)

作者： H. Bischof H. Wildenauer A. Leonardis Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia

ISBN: (纸本)0769511430

Variations in illumination can have a dramatic effect on the appearance of an object in an image. In this paper we propose how to deal with illumination variations in eigenspace methods. We demonstrate that the eigenimages obtained by a training set under a single illumination condition (ambient light) can be used for recognition of objects taken under different illumination conditions. The major idea is to incorporate a set of gradient based filter banks into the eigenspace recognition framework. This can be achieved since the eigenimage coefficients are invariant for linearly filtered images (input and eigenimages). To achieve further illumination insensitivity we devised a robust procedure for coefficient recovery. The proposed approach has been extensively evaluated on a set of 2160 images and the results were compared to other approaches.

关键词： Lighting Nonlinear filters Principal component analysis image coding Object recognition Filtering Filter bank image recognition Information science image sampling

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An efficient depalletizing system based on 2D range imagery

An efficient depalletizing system based on 2D range imagery

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IEEE International Conference on Robotics and Automation (ICRA)

作者： D.K. Katsoulas D.I. Kosmopoulos Institute for Pattern Recognition and Image Processing University of Freiburg Freiburg im Breisgau Germany Department of electrical engineering division of Computer Science National and Technical University of Athens Athens Greece

ISBN: (纸本)0780365763

We propose an efficient approach towards the solution of the de-palletizing problem, based on active vision. We describe a system comprising an industrial robot and a time of flight laser sensor, which performs the depalletizing task in real time, and independently of lighting conditions. In our case, the target objects are solid boxes of known identical dimensions, neatly layered but with arbitrary orientation within a layer, which are all placed on a platform. The layered structure of the target platform allows for 2D imagery. The system locates the position of the boxes by tracking one of the corners they expose to the laser source. The system locates the desired corners by applying the scan line approximation technique, adapted to fit the needs of our application, to the 2D input data. The advantages of our system over existing applications are its simplicity, robustness, speed and ease of installation.

关键词： Robustness Service robots Humans pattern recognition image processing Computer science Robot sensing systems Sensor phenomena and characterization Solids Target tracking

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Video watermark technique in motion vector

Video watermark technique in motion vector

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Brazilian Symposium on Computer Graphics and image processing (SIBGRAPI)

作者： Jun Zhang Jiegu Li Ling Zhang Superieure des Telecommunications TSI Paris France Institute of Image Processing and Pattern Recognition. Shanghai Jiaotong University Shanghai China Department of Electronics Jingdezhen Comprehensive College Jiangxi China

In this paper, we propose a video watermarking technique to hide copyright information in MPEG motion vector. In this method, watermark is embedded in larger value motion vectors, and specially in the less phase angle changed component. Then, the motion vector is modified into a new bitstream from which the watermark information can be easily retrieved. From the experimental results, it indicates that to embed watermark in motion vector has the advantage of little degrading the video quality, little influence on the MPEG decoding speed, capability to embed watermark in a short video sequence, and can be used to watermark on both the uncompressed and compressed video sequence.

关键词： Watermarking Video compression Video sequences Information retrieval Transform coding image coding Copyright protection Random number generation Redundancy image processing

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Memory efficient fingerprint verification

Memory efficient fingerprint verification

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IEEE International Conference on image processing

作者： C. Beleznai H. Ramoser B. Wachmann J. Birchbauer H. Bischof W. Kropatsch Advanced Computer Vision Austrian Research Centre Seibersdorf Vienna Austria Programm-und Systementwicklung Siemens AG Österreich Graz Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

Fingerprint recognition and verification are often based on local fingerprint features, usually ridge endings or terminations, also called minutiae. By exploiting the structural uniqueness of the image region around a minutia, the fingerprint recognition performance can be significantly enhanced. However, for most fingerprint images the number of minutia image regions (MIRs) becomes dramatically large, which imposes - especially for embedded systems - an enormous memory requirement. Therefore, we are investigating different algorithms for compression of minutia regions. The requirement for these algorithms is to achieve a high compression rate (about 20) with minimum loss in the matching performance of minutia image region matching. We investigate the matching performance for compression algorithms based on the principal component and the wavelet transformation. The matching results are presented in form of normalized ROC curves and interpreted in terms of compression rates and the MIR dimension.

关键词： Fingerprint recognition image coding Computer vision image recognition image processing image matching Embedded system Performance loss Biometrics Character recognition

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Handwritten Chinese character segmentation using a two-stage approach

Handwritten Chinese character segmentation using a two-stage...

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International Conference on Document Analysis and recognition

作者： Shuyan Zhao Zheru Chi Pengfei Shi Qing Wang Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China Centre for Multimedia Signal Processing Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science and Engineering Northwestern Polytechnical University Xi'an China

ISBN: (纸本)0769512631

Correct segmentation of handwritten Chinese characters is crucial to the successful recognition. However, because of the many difficulties involved, little work has been done in this area. In this paper, a two-stage approach is addressed to segment unconstrained handwritten Chinese character strings. A string is first coarsely segmented according to the background skeleton and vertical projection after a proper image preprocessing. At the fine segmentation stage that follows, the strokes that may contain segmentation points are first identified. The feature points are then extracted from candidate strokes and taken as segmentation point candidates through each of which a segmentation path may be formed. Geometric features are extracted and fuzzy decision rules learned from examples are used to evaluate the segmentation paths. By using this two-stage segmentation approach, we can achieve both good performance and efficiency in segmenting unconstrained handwritten Chinese characters.

关键词： image segmentation Character recognition pattern recognition Handwriting recognition Signal processing image processing Computer science Electronic mail image recognition Skeleton

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Preface

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2001年 2130卷 v页

作者： Dorffner, Georg Bischof, Horst Hornik, Kurt University of Vienna Dept. of Mecidal Cybernetics and Artificial Intelligence Freyung 6/2 Vienna Austria Technical University of Vienna Institute for Computer Aided Automation Pattern Recognition and Image Processing Group Favoritenstr. 9/1832 Vienna Austria Wirtschaftsuniversität Wien Institut für Statistik Augasse 2-6 Wien Austria

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