
Graph-Based Representations in Pattern Recognition
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The 34 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on graph-based representation and characterization, graph matching, classification, and querying, graph-based learning, graph-based segmentation, and applications.
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Content
- Title Page
- Preface
- Organization
- Table of Contents
- Graph Representation and Characterization
- A Global Method for Reducing Multidimensional Size Graphs
- Introduction
- Basic Definitions
- A Global Method for Reducing (G, ?): the L-Reduction
- Experimental Results
- Conclusion
- References
- Graph Descriptors from B-Matrix Representation
- Introduction
- Graph B-Matrices
- Pattern Vectors from B-Matrices
- Experiments
- Artificial Graphs
- Satellite Photos
- Conclusions
- References
- Dimensionality Reduction for Graph of Words Embedding
- Introduction
- Graph of Words Embedding
- Motivation
- Embedding Procedure
- Vocabulary Construction
- Dimensionality and Sparsity
- Dimensionality Reduction
- Kernel Principal Component Analysis
- Independent Component Analysis
- Experimental Results
- Databases
- Experimental Setup
- Results
- Conclusions
- References
- Entropy versus Heterogeneity for Graphs
- Introduction
- Graph Representation and the von Neumann Entropy
- Graph Heterogeneity Index and H Plot
- Experiments
- Conclusion
- References
- Learning Generative Graph Prototypes Using Simplified von Neumann Entropy
- Introduction
- Probabilistic Framework
- Model Coding Using MDL
- Expectation-Maximization
- Experiments
- Conclusion
- References
- Information-Geometric Graph Indexing from Bags of Partial Node Coverages
- Introduction
- Subgraph Indexation
- Partial Node Coverages
- Spectral Descriptors in Tangent Space
- Encoding Graphs in Tangent Space
- Bypass IT Dissimilarity Measures
- Henze-Penrose Divergence
- Total Variation k-dP Divergence
- Experiments
- Conclusions
- References
- Maximum Likelihood for Gaussians on Graphs
- Introduction
- Graph Orbifolds
- Quotient Gaussians on Graphs
- Maximum-Likelihood
- Experiments
- Conclusion
- References
- Towards Performance Evaluation of Graph-Based Representation
- Introduction
- Graph-Based Representation
- Graph Based on Points of Interest
- Region Adjacency Graph
- Skeleton Graph
- Spatial Relation Graph
- Discussion
- Empirical Impact of the Graph-Based Representation
- Data
- Experimental Setup
- Results
- Conclusion
- References
- Graph Matching, Classification, and Querying
- Measuring the Distance of Generalized Maps
- Introduction
- Generalized Maps and (Sub)Map Isomorphism
- Definition of a Distance Measure for Generalized Maps
- Algorithm for Approximating the nG-Map Distance
- Choice of a Couple of Darts (Line 5)
- Propagation of a Couple of Darts to Ensure Consistency(Line 6)
- Update of Cand with Respect to m' (Line 10)
- First Experimental Results
- Conclusion
- References
- Aggregated Search in Graph Databases: Preliminary Results
- Introduction
- Preliminaries
- Graph Aggregation for Query Processing Framework
- Maximum Common Subgraph Detection
- Query Generation
- Performance Evaluation
- Conclusions
- References
- Speeding Up Graph Edit Distance Computation through Fast Bipartite Matching
- Introduction
- Graph Edit Distance
- Bipartite Graph Matching by Assignment Algorithms
- Assignment Algorithms
- Bipartite Matching
- Experimental Results
- Assignment Algorithms on Randomly Generated Float Matrices
- Bipartite Matching on the IAM Data Sets
- Conclusion and Future Work
- References
- Two New Graph Kernels and Applications to Chemoinformatics
- Introduction
- Kernel from Edit Distance
- Incoming Data
- Treelet Kernel
- Computing Embedded Distribution
- Definition of Treelet Kernel
- Experiments
- Conclusion
- References
- Generalized Learning Graph Quantization
- Introduction
- Graph Orbifolds
- Learning Graph Quantization
- LGQ
- LGQ2.1
- Generalized LGQ
- Generalized Relevance LGQ
- Robust Soft LGQ
- Experiments
- Data
- Experimental Setup
- Results
- Conclusion
- References
- Parallel Graduated Assignment Algorithm for Multiple Graph Matching Based on a Common Labelling
- Introduction
- Multiple Graph Matching and Computer Architecture
- Attributed Graphs and Multiple Graph Matching
- Computer Architecture and Programming Model
- Desktop Computer Architecture
- Parallel Programming Model
- A Parallel Solution for the Graph Matching Problem
- Parallel Pf Computation
- Parallel Computation of Approximate Q Matrix
- Parallel Computation of Ph Matrix
- Experimental Evaluation
- Conclusions and Future Work
- References
- Smooth Simultaneous Structural Graph Matching and Point-Set Registration
- Introduction
- A Mixture Model
- Expectation Maximization
- Expectation
- Maximum Likelihood Affine Registration Parameters
- Maximum Likelihood Correspondence Indicators
- Outlier Rejection
- Experiments and Results
- Conclusions
- References
- Automatic Learning of Edit Costs Based on Interactive and Adaptive Graph Recognition
- Introduction
- Error-Tolerant Graph Matching Based on Edit Operations
- Labelling Space Based on $K_n$ and $K_e$ Values
- Classical Graph Recognition Paradigm
- Interactive Graph Recognition Paradigm
- Adaptive Graph Learning
- Practical Evaluation
- Conclusions and Future Work
- References
- Exploration of the Labelling Space Given Graph Edit Distance Costs
- Introduction
- Basic Notions
- Exploring the Labelling Space
- Computing the Discrete Labelling Space Using an Optimal Graph Matching Algorithm
- Computing $K^min_e$
- Computing $K^MAX_e$
- Graduated Assignment Algorithm for Computing the Grid
- Experiments
- Conclusions
- References
- Graph Matching Based on Dot Product Representation of Graphs
- Introduction
- Dot Product Representation of Graphs (DPRG)
- Dot Product Representation of Graphs
- Dot Product Representation of Graphs with Missing Data
- Graph Matching Based on DPRG
- Initialization
- Association Graph (AG)
- Missing Correspondences Recovery by DPRG
- Experiments
- Synthetic Data Experiments
- Real-World Data
- Conclusions
- Reference
- Indexing with Well-Founded Total Order for Faster Subgraph Isomorphism Detection
- Introduction
- Related Work
- Definitions and Notations
- Algorithm
- Proof of Completeness
- Complexity Analysis
- Evaluation
- Conclusions and Future Work
- References
- Graph-Based Segmentation
- Graph Transduction as a Non-cooperative Game
- Introduction
- Non-cooperative Games and Nash Equilibria
- Graph Transduction Game (GTG)
- Defining Payoff Functions
- Computing Nash Equilibria
- Experimental Results
- Experiments with Symmetric Similarities
- Experiments with Asymmetric Similarities
- Summary and Discussion
- References
- A Graph-Based Approach to Feature Selection
- Introduction
- Dominant-Set Clustering Algorithm
- Feature Selection Using Dominant-Set Clustering
- Experiments and Comparisons
- Conclusions
- References
- Spatio-Temporal Extraction of Articulated Models in a Graph Pyramid
- Introduction
- Paper Outline
- Recall: Irregular Graph Pyramids
- Rigid Part Extraction
- Determine Points of Articulation
- Generation of Hypotheses for Points of Articulation
- Verification and Selection of Hypotheses
- Experiments
- Conclusion
- References
- Semi-supervised Segmentation of 3D Surfaces Using a Weighted Graph Representation
- Introduction
- Weighted Graph-Based Seeded Segmentation
- Graph Creation
- Seeding and Greedy Growing
- Experimental Validation
- Quantitative Evaluation
- Qualitative Evaluation and Running Time
- Conclusions
- References
- Convexity Grouping of Salient Contours
- Introduction
- Grouping Element Extraction and Graph Construction
- Salient Contour Grouping
- Contour Saliency Measure
- Beam Search
- Multiple Contour Extraction
- Results
- Conclusions
- References
- Hierarchical Interactive Image Segmentation Using Irregular Pyramids
- Introduction
- Combinatorial Image Pyramids
- Interactive Operations on Pyramids
- Modifying Operations
- Building Segmentation
- Segmentation Results
- Discussion
- Conclusion
- References
- Tiled Top-Down Pyramids and Segmentation of Large Histological Images
- Introduction
- Top-Down Framework
- Topological Maps
- Tiled Topological Maps
- Tiled Top-Down Pyramids
- Segmentation Scheme
- Application for Large Histological Images Segmentation
- Conclusion
- References
- Segmentation of Similar Images Using Graph Matching and Community Detection
- Introduction
- Methodology
- Graph Generation
- Graph Matching
- Community Detection
- Image Label Propagation
- Experimental Results
- Conclusion
- References
- Applications
- Automatic Street Graph Construction in Sketch Maps
- Introduction
- Related Work
- Street Graph Detection
- Preprocessing
- Line Segment Detection
- Graph Creation
- Results
- Conclusion and Future Work
- References
- People Re-identification by Graph Kernels Methods
- Introduction
- Graph-Based Object Representation
- Comparisons between Objects by Means of Graph Kernels
- From Graph Edit Distance to Graph Kernels
- Novelty Detection and Person Re-identification
- Experimental Results
- Conclusions
- References
- Automatic Labeling of Handwritten Mathematical Symbols via Expression Matching
- Introduction
- Graph Representation of an Expression
- Expression Matching
- Experimental Results
- Concluding Remarks
- References
- Structure-Based Evaluation Methodology for Curvilinear Structure Detection Algorithms
- Introduction
- Drawbacks of Non-structural Performance Evaluation
- Structure-Based Evaluation Methodology
- Graph Matching
- Quality Measures
- Choosing Parameter Values
- Experimental Results
- Synthetic Data
- STARE Database
- Further Validations
- Conclusion
- References
- Keygraphs for Sign Detection in Indoor Environments by Mobile Phones
- Introduction
- Mobile Keygraph System
- Building Image Dataset
- Localization
- Keygraphs
- Experimental Results
- Conclusion
- References
- Classification of Graph Sequences Utilizing the Eigenvalues of the Distance Matrices and Hidden Markov Models
- Introduction
- Stochastic and Functional Principles
- Hidden Markov Models
- Gaussian Mixture Models
- Application Data and Selected Features
- Data Collection
- Graph and Feature Extraction
- Experimental Settings
- Settings of the HMMs and GMMs
- Adequacy and Performance of the Features
- Summary
- References
- Using Kernels on Hierarchical Graphs in Automatic Classification of Designs
- Introduction
- Hierarchical Graphs in Design Representation
- A Kernel on Hierarchical Graphs
- Experiments and Results
- Conclusions and Future Research
- References
- Author Index
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