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共 197 条记录，以下是111-120 订阅

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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...

引用

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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On Lipschitz embeddings of graphs

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12th international Conference on Knowledge-based Intelligent Information and Engineering Systems

作者： Riesen, Kaspar Bunke, Horst Univ Bern Inst Comp Sci & Appl Math CH-3012 Bern Switzerland

ISBN: (纸本)9783540855620

In pattern recognition and related fields, graph based representations offer a versatile alternative to the widely used feature vectors. therefore, an emerging trend of representing objects by graphs can be observed. this trend is intensified by the development of novel approaches in graph based machine learning, such as graph kernels or graph embedding techniques. these procedures overcome a major drawback of graphs, which consists in a serious lack of algorithms for classification and clustering. the present;paper is inspired by the idea of representing graphs by means of dissimilarities and extends previous work to the more general setting of Lipschitz embeddings. In all experimental evaluation we empirically confirm that classifiers relying oil the original graph distances call be outperformed by a classification system using the Lipschitz embedded graphs.

关键词： pattern recognition

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Proceedings of the Poster and Demonstration Session at the 7th international Semantic Web Conference, ISWC 2008

Proceedings of the Poster and Demonstration Session at the 7...

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7th international Semantic Web Conference, ISWC 2008

the proceedings contain 87 papers. the topics discussed include: BitMat: a main-memory bit matrix of RDF triples for conjunctive triple pattern queries;progress report from the RDB2RDF XG;optimizing SPARQL queries over disparate RDF data sources through distributed semi-joins;visualization of the search results of the semantic web search engines;a bootstrapping architecture for integration of relational databases to the semantic web;semantic framework for complex knowledge domains;Edhibou: a customizable interface for decision support in a semantic portal;MDS++: supporting ontology-based dynamic classification in websphere metadata server;graph-theoretic analysis of collaborative knowledge bases in natural language processing;CMAPS supporting the development of OWL ontologies;OmniCat: automatic text classification with dynamically defined categories;and BioPortal: a web repository for biomedical ontologies and data resources.

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On the combination of ridgelets descriptors for symbol recognition

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7th international workshop on graphics recognition, GREC 2007

作者： Terrades, O. Ramos Valveny, E. Tabbone, S. Computer Vision Center Spain Dept. Computer Science Universitat Autònoma de Barcelona Spain LORIA-Université Nancy 2 France

ISBN: (纸本)3540881840

In this paper we propose an original solution to combine the scales of multi-resolution shape descriptors. More precisely, a classifier fusion scheme is applied to a set of shape descriptors obtained from the ridgelets transform. the Ridgelets coefficients are grouped into different descriptors according to their resolution. then a classifier is trained for each descriptor and a final classification is obtained using the classifier fusion scheme. We have applied this approach to symbol recognition using the GREC 2003 database. In this perspective, we increase the recognition rates of previous works on ridgelets-based descriptors. © 2008 Springer-Verlag Berlin Heidelberg.

关键词： pattern recognition

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Structural, Syntactic, and Statistical pattern recognition 2008

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丛书名： Lecture Notes in Computer Science

2008年

作者： Niels da Vitoria Lobo Takis Kasparis Michael Georgiopoulos Fabio Roli James Kwok Georgios C. Anagnostopoulos Marco Loog

ISBN: (数字)9783540896890

ISBN: (纸本)9783540896883

this book constitutes the refereed proceedings of the 12th international workshop on Structural and Syntactic pattern recognition, SSPR 2008 and the 7th international workshop on Statistical Techniques in pattern recognition, SPR 2008, held jointly in Orlando, FL, USA, in December 2008 as a satellite event of the 19th international Conference of pattern recognition, ICPR 2008. the 56 revised full papers and 42 revised poster papers presented together with the abstracts of 4 invited papers were carefully reviewed and selected from 175 submissions. the papers are organized in topical sections on graph-based methods, probabilistic and stochastic structural models for PR, image and video analysis, shape analysis, kernel methods, recognition and classification, applications, ensemble methods, feature selection, density estimation and clustering, computer vision and biometrics, pattern recognition and applications, pattern recognition, as well as feature selection and clustering.

关键词： pattern recognition systems Congresses.

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Moment-based Techniques for Image Retrieval

Moment-Based Techniques for Image Retrieval

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international workshop on Database and Expert Systems Applications

作者： Cecilia Di Ruberto Andrea Morgera Dipartimento di Matematica e Informatica Universitá di Cagliari Italy

In this paper we analyze some shape-based image retrieval methods which use different types of geometric and algebraic moments and Fourier descriptors. Moments have been widely used in pattern recognition applications to describe the geometrical characteristics of different objects. they provide fundamental geometric properties (e.g. area, centroid, moment of inertia, etc.). We consider various description techniques: Hu, Flusser and Taubin invariants, Legendre and Zernike moments, Generic Fourier Descriptors (GFD). the set of absolute orthogonal (i.e. rotation) moment invariants defined by Hu can be used for scale, position, and rotation invariant pattern identification. Flusser' s complete set of invariants appears as a particular case, with invariance only to rotation. the Taubin's affine moment invariants introduce the concept of covariant matrix. Legendre moments are based on orthogonal Legendre polynomials and are not invariant under image rotation. Zernike moments consist of a set of complex polynomials that form a complete orthogonal set over the interior of the unit circle. GFDs are derived by applying a modified polar Fourier transform on shape image. We have applied the retrieval methods on a collection of images chosen from MPEG7 database. the image retrieval performance of each method is described by the precision-recall graph. In the paper we propose a novel approach that combines the described techniques after a coarse partitioning of the image dataset by their morphological features. the proposed approach provides much better performance than each method described above.

关键词： Shape pattern recognition Manganese Polynomials Image retrieval Image recognition Covariance matrix

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graph embedding in vector spaces by means of prototype selection

Graph embedding in vector spaces by means of prototype selec...

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

作者： Riesen, Kaspar Neuhaus, Michel Bunke, Horst Univ Bern Dept Comp Sci Neubruckstr 10 CH-3012 Bern Switzerland

ISBN: (纸本)9783540729020

the field of statistical pattern recognition is characterized by the use of feature vectors for pattern representation, while strings or, more generally, graphs are prevailing in structural pattern recognition. In this paper we aim at bridging the gap between the domain of feature based and graph based object representation. We propose a general approach for transforming graphs into n-dimensional real vector spaces by means of prototype selection and graph edit distance computation. this method establishes the access to the wide range of procedures based on feature vectors without loosing the representational power of graphs. through various experimental results we show that the proposed method, using graph embedding and classification in a vector space, outperforms the tradional approach based on k-nearest neighbor classification in the graph domain.

关键词： pattern recognition

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Computing homology group generators of images using irregular graph pyramids

Computing homology group generators of images using irregula...

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

作者： Peltier, S. Ion, A. Haxhimusa, Y. Kropatsch, W. G. Damiand, G. Vienna Univ Technol Fac Informat Pattern Recognit & Image Proc Grp A-1040 Vienna Austria Univ Poitiers SIC FRE 2731 CNRS Poitiers France

ISBN: (纸本)9783540729020

We introduce a method for computing homology groups and their generators of a 2D image, using a hierarchical structure i.e. irregular graph pyramid. Starting from an image, a hierarchy of the image is built, by two operations that preserve homology of each region. Instead of computing homology generators in the base where the number of entities (cells) is large, we first reduce the number of cells by a graph pyramid. then homology generators are computed efficiently on the top level of the pyramid, since the number of cells is small, and a top down process is then used to deduce homology generators in any level of the pyramid, including the base level i.e. the initial image. We show that the new method produces valid homology generators and present some experimental results.

关键词： Image analysis

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Generalized vs set median strings for histogram-based distances: Algorithms and classification results in the image domain

Generalized vs set median strings for histogram-based distan...

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

作者： Solnon, Christine Jolion, Jean-Michel Univ Lyon 1 CNRS INSA Lyon Nautibus LIRISUMR 5205 43 Bd 11 Novembre F-69622 Villeurbanne France

ISBN: (纸本)9783540729020

We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by its generalized median, i.e., the string -over the set of all possible strings- that minimizes the sum of distances to every string of the set, or by its set median, i.e., the string of the set that minimizes the sum of distances to every other string of the set. For the first two histogram-based distances, we show that the generalized median string can be computed efficiently;for the third one, which biased histograms with individual substitution costs, we conjecture that this is a NP-hard problem, and we introduce two different heuristic algorithms for approximating it. We experimentally compare the relevance of the three histogram-based distances, and the different statistical characterizations of sets of strings, for classifying images that are represented by strings.

关键词： pattern recognition

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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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