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International Conference on pattern recognition

作者： T. Melzer P. Kammerer E. Zolda Pattern Recognition & Image Processing Group University of Technology Vienna Vienna Austria

The arrangement of brush strokes is an important criterion in classifying portrait miniatures. In order to detect single brush strokes we used both a model based and a semi-parametric, neural network approach. The per... 详细信息

关键词： image edge detection Art image segmentation Humans Detectors Brightness pattern recognition Assembly Testing Interpolation

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Hierarchical classification of paintings using face- and brush stroke models

Hierarchical classification of paintings using face- and bru...

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International Conference on pattern recognition

作者： R. Sablatnig P. Kammerer E. Zolda Institute of Automation Pattern Recognition and Image Processing Group University of Technology Vienna Vienna Austria

It is often difficult to attribute works of art to a certain artist. In the case of paintings, radiological methods like X-ray and infra-red diagnosis, digital radiography, computer-tomography, etc. and color analyzes are employed to authenticate works of art. But all these methods do not relate certain characteristics of an art work to a specific artist-the artist's personal style. In order to study this personal style, we examine the "structural signature" based on brush strokes in particular in portrait miniatures. A computer-aided classification and recognition system for portrait miniatures is developed, which enables a semi-automatic classification based on brush strokes. A hierarchically structured classification scheme is introduced which separates the classification into three different levels of information: color, shape of region, and structure of brush strokes.

关键词： Painting Art Humans Face Automation pattern recognition image processing Postal services Trademarks Rhythm

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Minimizing the topological structure of line images 7th

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7th Joint IAPR International Workshop on Structural and Syntactic pattern recognition, SSPR 1998 and 2nd International Workshop on Statistical Techniques in pattern recognition, SPR 1998

作者： Kropatsch, Walter G. Burge, Mark Vienna University of Technology Institute of Automation 183/2 Pattern Recognition and Image Processing Group Treitlstr.3 WienA-1040 Austria Johannes Kepler University Institute of Systems Science Computer Vision Laboratory LinzA-4040 Austria

ISBN: (纸本)3540648585

We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) steps. A MLPP graph of a line image compliments the structural information in geometric graph representations like the run graph. Using such a graph and its dual, line image analysis systems can efficiently detect topological features like loops and holes and make use of relations like containment. © Springer-Verlag Berlin Heidelberg 1998.

关键词： Topology

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Object-detection with a varying number of eigenspace projections

Object-detection with a varying number of eigenspace project...

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14th International Conference on pattern recognition, ICPR 1998

作者： Reiter, Michael Matas, Jiri Pattern Recognition and Image Processing Group Institute for Automation Vienna University of Technology A-1040 Vienna Austria CVSSP School of EE IT and Mathematics University of Surrey Guildford Surrey GU2 5XH United Kingdom

ISBN: (纸本)0818685123

We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equivalently a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation of only a few eigen-projections. In this case the computation of MD can be immediately terminated. Regardless of the precise value of MD, the detection hypothesis (object from class Ω is detected) can be rejected. While provably obtaining results identical to the standard technique, we achieved a two- to three-fold speed-up in face detection experiments on images from the CMU database. © 1998 IEEE.

关键词： Face recognition

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Object-detection with a varying number of eigenspace projections

Object-detection with a varying number of eigenspace project...

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International Conference on pattern recognition

作者： M. Reiter J. Matas Pattern Recognition and Image Processing Group Institute for Automation University of Technology Vienna Vienna Austria CVSSP School of EE IT and Mathematics University of Surrey Guildford Surrey UK

We present a method allowing a significant speed-up of the eigen-detection method (detection based on principle component analysis). We derive a formula for an upper bound on the class-conditional probability (or equivalently a lower bound on the Mahalanobis distance) on which detection is based. Often, the lower bound of Mahalanobis distance (MD) reaches a preset threshold after computation of only a few eigen-projections. In this case the computation of MD can be immediately terminated. Regardless of the precise value of MD, the detection hypothesis (object from class /spl Omega/ is detected) can be rejected. While provably obtaining results identical to the standard technique, we achieved a two- to three-fold speed-up in face detection experiments on images from the CMU database.

关键词： Face detection Upper bound Object detection Lips pattern recognition image processing Automation Mathematics Electronic switching systems Read only memory

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A Region-Based Representation of images in MARS

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Journal of VLSI Signal processing Systems for Signal, image, and Video Technology 1998年第1-2期20卷 137-150页

作者： Servetto, Sergio D. Rui, Yong Ramchandran, Kannan Huang, Thomas S. Beckman Inst. Adv. Sci. and Technol. Univ. Illinois at Urbana-Champaign Urbana IL 61801 United States Universidad Nacional de La Plata Argentina Univ. Illinois at Urbana-Champaign United States Comp. Res. Adv. Applications Group IBM Argentina Argentina Image Formation and Processing Group Beckman Institute UIUC United States Department of Computer Science UNLP Argentina Dept. of Elec. and Comp. Engineering UIUC United States Multimedia Commun. Res. Department Bell Laboratories Murray Hill NJ United States Info. Sciences Research Department AT and T Labs. Florham Park NJ United States Department of Computer Science UIUC United States Southeast University China Tsinghua University China University of Illinois Urbana-Champaign IL United States Image Formation and Processing Group Beckman Inst. Advance Sci. Technol. UIUC United States Vis. Technol. Grp. of Microsoft Res. Redmond WA United States City College of New York United States Columbia University United States AT and T Bell Labs. United States Ctr. for Telecommunications Research Columbia University United States Elec. and Comp. Eng. Department United States Beckman Institute Coordinated Science Laboratory IL United States IEEE Signal Processing Society United States IEEE IMDSP Technical Committee United States IEEE Transactions on Image Proc. United States National Taiwan University Taipei Taiwan Massachusetts Inst. of Technology Cambridge MA United States Department of Electrical Engineering MIT United States School of Electrical Engineering United States Lab. for Info. and Signal Processing Purdue University United States Dept. of Elec. and Comp. Engineering United States Coordinated Science Laboratory United States Image Formation and Processing Group Beckman Inst. Adv. Sci. and Technol. United States MIT Lincoln Laboratory IBM Thomas J. Watson Research Center Rheinishes Landes Museum Bonn Germany Swiss Institutes of Technology Zurich Switzerland Swiss Institutes of Technology Lausanne S

We study the problem of representing images within a multimedia Database Management System (DBMS), in order to support fast retrieval operations without compromising storage efficiency. To achieve this goal, we propose new image coding techniques which combine a wavelet representation, embedded coding of the wavelet coefficients, and segmentation of image-domain regions in the wavelet domain. A bitstream is generated in which each image region is encoded independently of other regions, without having to explicitly store information describing the regions. Simulation results show that our proposed algorithms achieve coding performance which compares favorably, both perceptually and objectively, to that achieved using state-of-the-art image/video coding techniques while additionally providing region-based support.

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Stereo correspondences in scale space 3rd

Stereo correspondences in scale space

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3rd Asian Conference on Computer Vision, ACCV 1998

作者： Menard, Christian Pattern Recognition and Image Processing Group Vienna University of Technology TreitlstraBe 3/183/2 ViennaA-1040 Austria

ISBN: (纸本)3540639306

A central problem in stereo matching using correlation techniques lies in selecting the size of the search window. Small windows contain only a small number of data points, and thus are very sensitive to noise and therefore result in false matches. Whereas large search windows contain data from two or more different objects or surfaces, thus the estimated disparity is not accurate due to different projective distortions in the left and the right image. The new method introduces a continuous scale parameter for the matching process. It allows the adaption of the scale for every individual region and overcomes the drawbacks of fixed window sizes which is impressively demonstrated by the experimental results. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Stereo image processing

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Adaptive stereo matching in correlation scale-space 9th

Adaptive stereo matching in correlation scale-space

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9th International Conference on image Analysis and processing, ICIAP 1997

作者： Menard, Christian Kropatsch, Walter G. Pattern Recognition and Image Processing Group Vienna University of Technology Treitlstraße 3/183/2 ViennaA-1040 Austria

ISBN: (纸本)3540635076

Stereo computes the distance of objects, "their depth", from two images of two cameras using the triangulation principle. Points of imaged objects are mapped in different locations in the two stereo images. A central problem in stereo matching using correlation techniques lies in selecting the size of the search window. Small windows contain only a small number of data points, and thus are very sensitive to noise and therefore result in false matches. Whereas large search windows contain data from two or more different objects or surfaces, thus the estimated disparity is not accurate due to different projective distortions in the left and the right image. The new method introduces a continuous scale parameter for the matching process. It allows the adaption of the scale for every individual region and overcomes the drawbacks of fixed window sizes which is impressively demonstrated by the experimental results. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Stereo image processing

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Stereo matching using M-estimators 7th

Stereo matching using M-estimators

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7th International Conference on Computer Analysis of images and patterns, CAIP 1997

作者： Menard, Christian Leonardis, Aleš Pattern Recognition and Image Processing Group Vienna University of Technology Treitlstraße 3/183/2 Vienna Austria University of Ljubljana Slovenia

ISBN: (纸本)3540634606

Stereo computation is just one of the vision problems where the presence of outliers cannot be neglected. Most standard algorithms make unrealistic assumptions about noise distributions, which leads to erroneous results that cannot be corrected in subsequent processing stages. In this work the standard area-based correlation approach is modified so that it can tolerate a significant number of outliers. The approach exhibits a robust behaviour not only in the presence of mismatches but also in the case of depth discontinuities. Experimental results are given on synthetic and real images. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Statistics

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Computational complexity reduction in eigenspace approaches 7th

Computational complexity reduction in eigenspace approaches

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7th International Conference on Computer Analysis of images and patterns, CAIP 1997

作者： Leonardis, Aleš Bischof, Horst Vienna University of Technology Institute for Automation Pattern Recognition and Image Processing Group Treitlstraße 3/1832 ViennaA-1040 Austria University of LjubIjana Tržaška 25 LjubljanaSI-1001 Slovenia

ISBN: (纸本)3540634606

Matching of appearance-based object representations using eigenimages is computationally very demanding. Most commonly, to recognize an object in an image, parts of the input image are projected onto the eigenspace and the recovered coefficients indicate the presence or absence of a particular object. In general, the process is sequentially applied to the entire image. In this paper we discuss how to alleviate the problems related to complexity. First, we propose to use a focus-ofattention (FOA) detector which is intended to select candidate areas of interest with minimal computational effort. Only at these areas we then recover the coefficients of eigenimages. Secondly, we propose to employ a multiresolution approach. However, this requires that we depart from the standard way of calculating the coefficients of the eigenimages which relies on the orthogonality property of eigenimages. Instead we calculate them by solving a system of linear equations. We show the results of our approach on real data. © Springer-Verlag Berlin Heidelberg 1997.

关键词： Computers

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