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9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013

作者： De Sousa, Samuel Artner, Nicole M. Kropatsch, Walter G. Vienna University of Technology Pattern Recognition and Image Processing Group Vienna Austria

ISBN: (纸本)9783642382208

graph centrality has been extensively applied in Social Network Analysis to model the interaction of actors and the information flow inside a graph. In this paper, we investigate the usage of graph centralities in the Shape Matching task. We create a graph-based representation of a shape and describe this graph by using different centrality measures. We build a Naive Bayes classifier whose input feature vector consists of the measurements obtained by the centralities and evaluate the different performances for each centrality. © 2013 Springer-Verlag.

关键词： graphic methods

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Approximating TSP solution by MST based graph pyramid

Approximating TSP solution by MST based graph pyramid

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6th international workshop on graph-based representations in pattern recognition

作者： Haxhimusa, Yll Kropatsch, Walter G. Pizlo, Zygmunt Ion, Adrian Lehrbaum, Andreas Vienna Univ Technol Fac Informat Inst Comp Aided Automat Pattern Recognit & Image Proc Grp A-1040 Vienna Austria Purdue Univ Dept Physiol Sci W Lafayette IN 47907 USA

ISBN: (纸本)9783540729020

the traveling salesperson problem (TSP) is difficult to solve for input instances with large number of cities. Instead of finding the solution of an input with a large number of cities, the problem is approximated into a simpler form containing smaller number of cities, which is then solved optimally. graph pyramid solution strategies, in a bottom-up manner using Boruvka's minimum spanning tree, convert a 2D Euclidean TSP problem with a large number of cities into successively smaller problems (graphs) with similar layout and solution, until the number of cities is small enough to seek the optimal solution. Expanding this tour solution in a top-down manner to the lower levels of the pyramid approximates the solution. the new model has an adaptive spatial structure and it simulates visual acuity and visual attention. the model solves the TSP problem sequentially, by moving attention from city to city with the same quality as humans. graph pyramid data structures and processing strategies are a plausible model for finding near-optimal solutions for computationally hard pattern recognition problems.

关键词： graph theory

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Structural, Syntactic, and Statistical pattern recognition - Joint IAPR international workshop, SSPR and SPR 2010, Proceedings

Structural, Syntactic, and Statistical Pattern Recognition -...

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7th Joint IAPR international workshop on Structural, Syntactic, and Statistical pattern recognition, SSPR and SPR 2010

ISBN: (纸本)3642149790

the proceedings contain 74 papers. the topics discussed include: from region based image representation to object discovery and recognition;structural patterns in complex networks through spectral analysis;graph embedding using an edge-based wave kernel;combining elimination rules in tree-based nearest neighbor search algorithms;entropy-based variational scheme for fast Bayes learning of Gaussian mixtures;learning graph quantization;high-dimensional spectral feature selection for 3D object recognition based on Reeb graphs;dissimilarity-based multiple instance learning;a game theoretic approach to learning shape categories and contextual similarities;a comparison between two representatives of a set of graphs: median vs. barycenter graph;automatic traffic monitoring from satellite images using artificial immune system;and graph embedding based on nodes attributes representatives and a graph of words representation.

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A graph-based concept for spatiotemporal information in cognitive vision

A graph-based concept for spatiotemporal information in cogn...

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5th IAPR international workshop on graph-based representations in pattern recognition, GbRPR 2005

作者： Ion, Adrian Haxhimusa, Yll Kropatsch, Walter G. Pattern Recognition and Image Processing Group 183/2 Institute for Computer Aided Automation Vienna University of Technology Austria

A concept relating story-board description of video sequences with spatio-temporal hierarchies build by local contraction processes of spatio-temporal relations is presented. Object trajectories are curves in which their ends and junctions are identified. Junction points happen when two (or more) trajectories touch or cross each other, which we interpret as the "interaction" of two objects. Trajectory connections are interpreted as the high level descriptions. © Springer-Verlag Berlin Heidelberg 2005.

关键词： graph theory

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A fast construction of the distance graph used for the classification of heterogeneous electron microscopic projections

A fast construction of the distance graph used for the class...

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6th international workshop on graph-based representations in pattern recognition

作者： Kalinowski, Miroslaw Daurat, Alain Herman, Gabor T. CUNY Grad Ctr Dept Comp Sci 365 5th Ave New York NY 10016 USA Univ Louis Pasteur Strasbourg 1 LSIIT CNRS UMR 7005Pole API F-67400 Illkirch Graffenstaden France

ISBN: (纸本)9783540729020

It has been demonstrated that the difficult problem of classifying heterogeneous projection images, similar to those found in 3D electron microscopy (3D-EM) of macromolecules, can be successfully solved by finding an approximate Max k-Cut of an appropriately constructed weighted graph. Despite of the large size (thousands of nodes) of the graph and the theoretical computational complexity of finding even an approximate Max k-Cut, an algorithm has been proposed that finds a good (from the classification perspective) approximate solution within several minutes (running on a standard PC). However, the task of constructing the complete weighted graph (that represents an instance of the projection image classification problems) is computationally expensive. Due to the large number of edges, the computation of edge weights can take tens of hours for graphs containing several thousand nodes. We propose a method, which utilizes an early termination technique, to significantly reduce the computational cost of constructing such graphs. We compare, on synthetic data sets that resemble projection sets encountered in 3D-EM, the performance of our method with that of a brute-force approach and a method based on nearest neighbor search.

关键词： graph theory

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pattern recognition on aerospace images using deep neural networks 7

Pattern recognition on aerospace images using deep neural ne...

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7th IEEE international workshop on Metrology for AeroSpace (MetroAeroSpace)

作者： Saetchnikov, Ivan Skakun, Victor Tcherniavskaia, Elina Belarusian State Univ Radio Phys Dept Minsk BELARUS Belarusian State Univ Phys Dept Minsk BELARUS

ISBN: (纸本)9781728166360

pattern recognition is one of the most important tasks in aerospace image processing. Various methods based on convolutional neural networks attain state-of-the-art accuracy;however, their effectiveness on exact images is influenced by the chosen architecture and its training parameters. this work present methods based on convolutional neural networks for pattern recognition on the aerospace images. A possibility for objects segmentation into ten classes is demonstrated on example of the multispectral images from the World View 3 satellite. Four networks with different architectures were built, trained and optimized parametrically based on the auto-encoder neural networks. Segmentation results has been analyzed by means of three parameters: training Jacard Index, testing Jacard Index and weight numbers. the positive impact of the properly selected shearing augmentation on extension of a small marked dataset is discussed. the influence of the nonequilibrium classes on the segmentation accuracy and how to account this feature during training of deep neural networks is pointing out.

关键词： convolutional neural network deep learning unmanned aerial vehicle pattern recognition segmentation autoencoder aerospace image

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pattern recognition for the time-of-propagation counter

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NUCLEAR INSTRUMENTS & MEthODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 2011年第1期639卷 252-255页

作者： Staric, M. Jozef Stefan Inst Ljubljana Slovenia

In the barrel region at the Belle II detector, a time-of-propagation (TOP) counter is foreseen for particle identification. In this counter the particle identity is determined from a complicated pattern in the time and the position of Cherenkov photon hits. We present an extended likelihood method for particle identification, which is based on an analytical construction of the likelihood function. (C) 2010 Elsevier B.V. All rights reserved.

关键词： TOP counter Particle identification Extended likelihood method

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Joint IAPR international workshops on 10th Structural, Syntactic, and Statistical pattern recognition, SSPR 2004 and 5th international workshop on Statistical Techniques in pattern recognition, SPR 2004

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Joint IAPR 10th international workshop on Structural and Syntactic pattern recognition, SSPR 2004 and 5th international workshop on Statistical Techniques in pattern recognition, SPR 2004

ISBN: (纸本)9783540225706

the proceedings contain 127 papers. the special focus in this conference is on Visual recognition, Detection, Contours, Lines and Paths. the topics include: Finding clusters and components by unsupervised learning;a demonstration on text data;the use of graph techniques for identifying objects and scenes in indoor building environments for mobile robots;graphical-based learning environments for pattern recognition;spectral analysis of complex laplacian matrices;a significant improvement of softassign with diffusion kernels;eigenspace method by autoassociative networks for object recognition;extraction of skeletal shape features using a visual attention operator;computing the cyclic edit distance for pattern classification by ranking edit paths;steady state random walks for path estimation;new variational framework for rigid-body alignment;an error-tolerant approximate matching algorithm for attributed planar graphs and its application to fingerprint classification;comparison of algorithms for web document clustering using graph representations of data;a syntactic pattern recognition approach to computer assisted translation;a general methodology for finite-state translation using alignments;a comparison of unsupervised shot classification algorithms for news video segmentation;diagnosis of lung nodule using the semivariogram function;distances between distributions;multiscale curvature assessment of postural deviations;learning people movement model from multiple cameras for behaviour recognition;a comparison of least squares and spectral methods for attributed graph matching and an auction algorithm for graph-based contextual correspondence matching.

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Motion Description with Local Binary pattern and Motion History Image: Application to Human Motion recognition

Motion Description with Local Binary Pattern and Motion Hist...

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7th IEEE international workshop on Haptic Audio Visual Environments and their Applications

作者： Guo, Ping Miao, Zhenjiang Beijing Jiaotong Univ Inst Informat Sci Beijing 100044 Peoples R China

ISBN: (纸本)9781424426683

this paper presents a new human motion recognition method based on motion history image (MHI) and local binary pattern (LBP). MHI describes human motion sequence in one gray level image and LBP extracts its texture features. LBP feature image is built and chi square distance is applied to compute matching cost. Experiments are conducted with encouraging results which show a success of applying LBP in motion recognition.

关键词： motion recognition motion history image local binary pattern

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Hierarchy construction schemes within the scale set framework

Hierarchy construction schemes within the scale set framewor...

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6th international workshop on graph-based representations in pattern recognition

作者： Pruvot, Jean-Hugues Brun, Luc CNRS UMR 6072 Image Team GREYC Lab 6 Blvd Marechal Juin F-14050 Caen France

ISBN: (纸本)9783540729020

Segmentation algorithms based on an energy minimisation framework often depend on a scale parameter which balances a fit to data and a regularising term. Irregular pyramids are defined as a stack of graphs successively reduced. Within this framework, the scale is often defined implicitly as the height in the pyramid. However, each level of an irregular pyramid can not usually be readily associated to the global optimum of an energy or a global criterion on the base level graph. this last drawback is addressed by the scale set framework designed by Guigues. the methods designed by this author allow to build a hierarchy and to design cuts within this hierarchy which globally minimise an energy. this paper studies the influence of the construction scheme of the initial hierarchy on the resulting optimal cuts. We propose one sequential and one parallel method with two variations within both. Our sequential methods provide partitions near an energy lower bound defined in this paper. Parallel methods require less execution times than the sequential method of Guigues even on sequential machines.

关键词： pattern recognition

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