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检索条件"任意字段=7th International Workshop on Graph-Based Representations in Pattern Recognition"

共 197 条记录，以下是41-50 订阅

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STIT: Spatio-Temporal Interaction Transformers for Human-Object Interaction recognition in Videos 26

STIT: Spatio-Temporal Interaction Transformers for Human-Obj...

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26th international Conference on pattern recognition / 8th international workshop on Image Mining - theory and Applications (IMTA)

作者： Almushyti, Muna Li, Frederick W. B. Univ Durham Dept Comp Sci Durham England Qassim Univ Educ Serv Buraydah Saudi Arabia

ISBN: (数字)9781665490627

ISBN: (纸本)9781665490627

Recognizing human-object interactions is challenging due to their spatio-temporal changes. We propose the Spatio-Temporal Interaction Transformer-based (STIT) network to reason such changes. Specifically, spatial transformers learn humans and objects context at specific frame time. Temporal transformer then learns the relations at a higher level between spatial context representations at different time steps, capturing long-term dependencies across frames. We further investigate multiple hierarchy designs in learning human interactions. We achieved superior performance on Charades, Something-Something v1 and CAD-120 datasets, comparing to baseline models without learning human-object relations, or with prior graph-based networks. We also achieved state-of-the-art accuracy of 95.93% on CAD-120 dataset [1] by employing RGB data only.

关键词： Deep learning Transformers pattern recognition Videos Context modeling

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Inside and outside within combinatorial pyramids

Inside and outside within combinatorial pyramids

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5th international workshop on graph-based representations in pattern recognition

作者： Brun, L Kropatsch, W ENSICAEN CNRS UMR 6072 GreYC F-14045 Caen France Vienna Univ Technol Inst Comp Aided Automat Pattern Recognit & Image Proc Grp A-1060 Vienna Austria

ISBN: (纸本)3540252703

Irregular pyramids are made of a stack of successively reduced graphs embedded in the plane. Such pyramids are often used within the segmentation and the connected component analysis frameworks to detect meaningful objects together with their spatial and topological relationships. the graphs reduced in the pyramid may be region adjacency graphs, dual graphs or combinatorial maps. Using any of these graphs each vertex of a reduced graph encodes a region of the image. Using simple graphs one edge between two vertices encodes the existence of a common boundary between two regions. Using dual graphs and combinatorial maps, each connected boundary segment between two regions is associated to one edge. Moreover, special edges called loops may be used to differentiate a special type of adjacency where one region surrounds the other. We show in this article that the loop information does not allow to distinguish inside and outside of the loop by local computations. We provide a method based on the combinatorial pyramid framework which uses the orientation explicitly encoded by combinatorial maps to determine inside and outside with local calculus.

关键词： graph theory

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Hierarchical Interactive Image Segmentation Using Irregular Pyramids

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8th IAPR-TC-15 international workshop on graph-based representations in pattern recognition (GbRPR)

作者： Gerstmayer, Michael Haxhimusa, Yll Kropatsch, Walter G. Vienna Univ Technol Inst Comp Graph & Algorithms Pattern Recognit & Image Proc Grp Vienna Austria

ISBN: (纸本)9783642208447

In this paper we describe modifications of irregular image segmentation pyramids based on user-interaction. We first build a hierarchy of segmentations by the minimum spanning tree based method, then regions from different (granularity) levels are combined to a final (better) segmentation with user-specified operations guiding the segmentation process. based on these operations the users can produce a final image segmentation that best suits their applications. this work can be used for applications where we need accuracy in image segmentation, in annotating images or creating ground truth among others.

关键词： Image segmentation

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A comparison of explicit and implicit graph embedding methods for pattern recognition

A comparison of explicit and implicit graph embedding method...

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

作者： Conte, Donatello Ramel, Jean-Yves Sidère, Nicolas Luqman, Muhammad Muzzamil Gaüzère, Benoît Gibert, Jaume Brun, Luc Vento, Mario Italy 64 Avenue Jean Portalis 37200 Tours France L3i Laboratory University of la Rochelle 17042 La Rochelle France GREYC UMR CNRS 6072 14000 Caen France

ISBN: (纸本)9783642382208

In recent years graph embedding has emerged as a promising solution for enabling the expressive, convenient, powerful but computational expensive graph based representations to benefit from mature, less expensive and efficient state of the art machine learning models of statistical pattern recognition. In this paper we present a comparison of two implicit and three explicit state of the art graph embedding methodologies. Our preliminary experimentation on different chemoinformatics datasets illustrates that the two implicit and three explicit graph embedding approaches obtain competitive performance for the problem of graph classification. © 2013 Springer-Verlag.

关键词： Classification (of information)

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graph-based representations in pattern recognition 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Donatello Conte Jean-Yves Ramel Pasquale Foggia

ISBN: (数字)9783030200817

ISBN: (纸本)9783030200800

this book constitutes the refereed proceedings of the 12th IAPR-TC-15 international workshop on graph-based Representation in pattern recognition, GbRPR 2019, held in Tours, France, in June 2019.;the 22 full papers included in this volume together with an invited talk were carefully reviewed and selected from 28 submissions. the papers discuss research results and applications at the intersection of pattern recognition, image analysis, and graph theory. they cover topics such as graph edit distance, graph matching, machine learning for graph problems, network and graph embedding, spectral graph problems, and parallel algorithms for graph problems.

关键词： pattern recognition Discrete Mathematics in Computer Science Computer graphics Algorithm Analysis and Problem Complexity Data Structures Artificial Intelligence

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graph-based representations in pattern recognition 1

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丛书名： Lecture Notes in Computer Science

1000年

作者： Walter G. Kropatsch Nicole M. Artner Yll Haxhimusa Xiaoyi Jiang

ISBN: (数字)9783642382215

ISBN: (纸本)9783642382208

this book constitutes the refereed proceedings of the 9th IAPR-TC-15 international workshop on graph-based representations in pattern recognition, GbRPR 2013, held in Vienna, Austria, in May 2013. the 24 papers presented in this volume were carefully reviewed and selected from 27 submissions. they are organized in topical sections named: finding subregions in graphs; graph matching; classification; graph kernels; properties of graphs; topology; graph representations, segmentation and shape; and search in graphs.

关键词： pattern recognition Image Processing and Computer Vision Computer Imaging, Vision, pattern recognition and graphics Computer graphics Discrete Mathematics in Computer Science Data Structures

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Joint IAPR international workshops on Structural and Syntactic pattern recognition and Statistical Techniques in pattern recognition, SSPR and SPR 1998.

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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

ISBN: (纸本)3540648585

the proceedings contain 113 papers. the special focus in this conference is on Structural Matching, Grammatical Inference and recognition of 2D and 3D Objects. the topics include: Error-tolerant graph matching;semantic content based image retrieval using object-process diagrams;pattern recognition methods in image and video databases;efficient matching with invariant local descriptors;integrating numerical and syntactic learning models for pattern recognition;synthesis of function-described graphs;marked subgraph isomorphism of ordered graphs;distance evaluation in pattern matching based on frontier topological graph;syntactic interpolation of fractal sequences;minimizing the topological structure of line images;genetic algorithms for structural editing;the noisy subsequence tree recognition problem;object recognition from large structural libraries;acquisition of 2-d shape models from scenes with overlapping objects using string matching;a taxonomy of occlusion in view signature ii representations;a survey of non-thinning based vectorization methods;a benchmark for raster to vector conversion systems;network-based recognition of architectural symbols;recovering image structure by model-based interaction map;an improved scheme to fingerprint classification;character recognition with k-head finite array automata;using semantics in matching cursive chinese handwritten annotations;concavity detection using a binary mask-based approach;structural indexing of line pictures with feature generation models;nonlinear covariance for multi-band image data;a neural network for image smoothing and segmentation;prototyping structural descriptions and neural network based learning of local compatibilities for segment grouping.

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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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Congratulations! Dual graphs Are Now Orientated! 1

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12th IAPR-TC15 workshop on graph-based representations in pattern recognition (GbRPR)

作者： Batavia, Darshan Kropatsch, Walter G. Casablanca, Rocio M. Gonzalez-Diaz, Rocio TU Wien Pattern Recognit & Image Proc Grp 193 03 Vienna Austria Univ Seville Appl Math 1 Seville Spain

ISBN: (数字)9783030200817

ISBN: (纸本)9783030200817;9783030200800

A digital image can be perceived as a 2.5D surface consisting of pixel coordinates and the intensity of pixel as height of the point in the surface. Such surfaces can be efficiently represented by the pair of dual plane graphs: neighborhood (primal) graph and its dual. By defining orientation of edges in the primal graph and use of Local Binary Patters (LBPs), we can categorize the vertices corresponding to the pixel into critical (maximum, minimum, saddle) or slope points. Basic operation of contraction and removal of edges in primal graph result in configuration of graphs with different combinations of critical and non-critical points. the faces of graph resemble a slope region after restoration of the continuous surface by successive monotone cubic interpolation. In this paper, we define orientation of edges in the dual graph such that it remains consistent with the primal graph. Further we deliver the necessary and sufficient conditions for merging of two adjacent slope regions.

关键词： Pixels

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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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