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检索条件"机构=Pattern Recognition and Image Processing"

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A modified dense displacement field estimation algorithm combined with block-matching method

A modified dense displacement field estimation algorithm com...

引用

International Conference on Signal processing Proceedings (ICSP)

作者： Guo Fengjun Yan Xin W. Philips Shi Penfei Institute of Image Processing & Pattern Recognition Shanghai Jiaotong University Shanghai China TELIN Department Ghent University Belgium

We presented a displacement field estimation algorithm based on a relaxed smoothness constraint; this algorithm can preserve discontinuities in the displacement field to some extent. Because image data is irregular and the images are noisy, the method produces some large residual errors in the residual maps. We propose an improved displacement field estimation algorithm which uses the displacement information obtained using block-matching to modify the matching result. Experimental results show, this leads to smaller residual error maps, without introducing block artefacts, as would happen in the case of simple block-matching when there is much noise in the background. Also the displacement filed using this method is more consistent than using a method without additional block-matching.

关键词： image motion analysis Mathematical model Computer vision image processing image matching pattern recognition Background noise Gradient methods Motion estimation Motion detection

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A new approach to finite wordlength coefficient fir digital filter design using the branch and bound technique 10

A new approach to finite wordlength coefficient fir digital ...

引用

2000 10th European Signal processing Conference, EUSIPCO 2000

作者： Belbachir, A.N. Boulerial, B. Belbachir, M.F. Signal and System Laboratory Electronic Institute U.S.T.O. B.P. 1505 El Mnouer Oran Algeria Vienna University of Technology Pattern Recognition and Image Processing Group Favritenstr. 9/1832 ViennaA-1040 Austria

ISBN: (纸本)9789521504433

It has been shown that the branch and bound technique is effective for the design of finite wordlength optimal digital filters. This technique is however expensive in computing time. In this paper, we present a robust branch and bound branching strategy named Sequential and Progressive Search, improving the design of filters on a large wordlength processor in a reasonable computing cost. The details of the algorithm and many examples are given and compared to the other methods. © 2000 EUSIPCO.

关键词： Digital filters

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Estimating the next sensor position based on surface characteristics

Estimating the next sensor position based on surface charact...

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International Conference on pattern recognition

作者： C. Liska R. Sablatnig Austrian Research Centre Seibersdorf Vienna Austria Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

ISBN: (纸本)0769507506

In order to reconstruct the viewable surface of an object completely, multiple views of the same object have to be used and integrated into a common coordinate system. One of the major problems of the 3D surface reconstruction using a turntable, is the varying resolution in the direction to the camera, due to the varying distance of object points to the rotational axis of the turntable. To guarantee a uniform object resolution, we calculate the next angle dynamically, depending on the entropy of the surface part actually acquired. To minimize the loss of information and to guarantee a uniform surface resolution, we derive a relation between the entropy and the next viewing angle, based on the profile sections acquired in the last two steps of the acquisition.

关键词： Sensor phenomena and characterization Surface reconstruction image reconstruction Cameras Entropy Position measurement Shape measurement Java pattern recognition image processing

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Robust spot fitting for genetic spot array images

Robust spot fitting for genetic spot array images

引用

IEEE International Conference on image processing

作者： H.-Y. Chen N. Brandle H. Bischof H. Lapp Pattern Recognition & Image Processing Group University of Technology Vienna Vienna Austria Novartis Research Institute Vienna Genetics Vienna Austria

Addresses the problem of reliably fitting parametric and semi-parametric models to high density spot array images obtained in gene expression experiments. The goal is to measure the amount of genetic material at specific spot locations. Many spots can be modelled accurately by a Gaussian shape. In order to deal with highly overlapping spots the authors use robust M-estimators. When the parametric method fails, they use a novel, robust semi-parametric method which can handle spots of different shapes accurately. They present the results for real data and compare the complexity of the two methods.

关键词： Robustness Genetics Shape image analysis Gene expression pattern recognition image processing Lapping Safety Noise shaping

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Fuzzy c-means in an MDL-framework

Fuzzy c-means in an MDL-framework

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International Conference on pattern recognition

作者： A. Selb H. Bischof 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)0769507506

In this paper we present a minimum description length (MDL) framework for fuzzy clustering algorithms. This framework enables us to find an optimal number of cluster centers. We applied our approach to the fuzzy c-means algorithm for which we designed a computationally efficient procedure. We report the results of our approach on a 2D clustering problem and on RGB color image segmentation.

关键词： Clustering algorithms Radial basis function networks Encoding Color image segmentation image recognition image processing Algorithm design and analysis Unsupervised learning pattern recognition

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Content based image retrieval using interest points and texture features

Content based image retrieval using interest points and text...

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15th International Conference on pattern recognition, ICPR 2000

作者： Wolf, Christian Jolion, Jean-Michel Kropatsch, Walter Bischof, Horst Vienna University of Technology Pattern Recognition and Image Processing Group Favoritenstraße 9/1832 Wien1040 Austria INSA de Lyon Laboratoire Reconnaissance de Formes et Vision 3 Avenue Albert Einstein Villeurbanne Cedex69626 France

ISBN: (纸本)0769507506

Content based image retrieval is the task of searching images from a database, which are visually similar to a given example image. We present methods for content based image retrieval based on texture similarity using interest points and Gabor features. Interest point detectors are used in computer vision to detect image points with special properties, which can be geometric (corners) or non-geometric (contrast etc.). Gabor functions and Gabor filters are regarded as excellent tools for feature extraction and texture segmentation. The article combines these methods and generates a textural description of images. Special emphasis is devoted to distance measures on texture descriptions. Experimental results of a query system are given. © 2000 IEEE.

关键词： Gabor filters

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Multiple eigenspaces by MDL

Multiple eigenspaces by MDL

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International Conference on pattern recognition

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

ISBN: (纸本)0769507506

We propose an approach to constructing multiple eigenspaces from a set of training images based on the minimum description length (MDL) principle. The main idea is to systematically build a redundant set of eigenspaces, which are treated as hypotheses that are then subject to a selection procedure. The selection procedure, based on the MDL principle, selects the final resulting set of eigenspaces as an optimal representation of the training set. We have tested the proposed method on a number of standard image sets, and the significance of the approach with respect to the recognition rate has been clearly demonstrated.

关键词： Testing image recognition Principal component analysis Information science image analysis image reconstruction pattern recognition image processing Robustness Robust control

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Nearness in digital images and proximity spaces

Nearness in digital images and proximity spaces

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9th International Conference on Discrete Geometry for Computer imagery, DGCI 2000

作者： Pták, Pavel Kropatsch, Walter G. CMP – Czech Technical University Center for Machine Perception Karlovo nám. 13 Praha 2121 35 Czech Republic Institute of Computer Aided Automation 183/2 Vienna University of Technology Pattern Recognition and Image Processing Group Favoritenstr.9 WienA-1040 Austria

ISBN: (纸本)3540413960

The concept of "nearness", which has been dealt with as soon as one started studying digital images, finds one of its rigorous forms in the notion of proximity space. It is this notion, together with "nearness preserving mappings", that we investigate in this paper. We first review basic examples as they naturally occur in digital topologies, making also brief comparison studies with other concepts in digital geometry. After this we characterize proximally continuous mappings in metric spaces. Finally, we show by example that the "proximite complexity" of a finite covering in a digital picture may be too high to be adequately depicted in a finite topological space. This combinatorial result may indicate another conceptual advantage of proximities over topologies. © Springer-Verlag Berlin Heidelberg 2000.

关键词： Topology

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Content based image retrieval using interest points and texture features

Content based image retrieval using interest points and text...

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International Conference on pattern recognition

作者： C. Wolf J.-M. Jolion W. Kropatsch H. Bischof Pattern Recognition and Image Processing Group University of Technology Vienna Wien Austria Laboratoire Reconnaissance de Formes et Vision INSA Lyon Villeurbanne France

ISBN: (纸本)0769507506

关键词： image retrieval Content based retrieval Information retrieval image databases Spatial databases Visual databases Detectors Computer vision Gabor filters Feature extraction

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Background mosaic from egomotion

Background mosaic from egomotion

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International Conference on pattern recognition

作者： R. Megret C. Saraceno W. Kropatsch École Normale Supérieure de Lyon Lyon France Starlab NV Brussels Belgium Pattern Recognition and Image Processing group University of Technology Vienna Vienna Austria

ISBN: (纸本)0769507506

A framework is presented that produces the mosaic corresponding to the background object of an image sequence. It is based on the dominant motion assumption, which states that the background has a parametric motion and occupies the main part of the images. The foreground objects are localised by their different motion. This localisation is computed together with the background motion in an iterative method. The regions corresponding to the background are then pasted onto the mosaic using classic methods adapted to object elimination or a new mosaicking method based on a striping that takes the foreground objects localisation into account.

关键词： image segmentation Pixel Parametric statistics pattern recognition image processing image sequences Iterative methods Video sequences Buildings Motion segmentation

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