
Pattern Recognition. ICPR International Workshops and Challenges
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Content
- Intro
- Foreword by General Chairs
- Preface
- Challenges
- ICPR Organization
- Contents - Part V
- IMTA VII - Workshop on Image Mining Theory and Applications
- IMTA-VII-2020: Workshop on Image Mining Theory and Applications
- Workshop Description
- Organization
- IMTA Chairs
- Scientific Committee
- The Study of Improving the Accuracy of Convolutional Neural Networks in Face Recognition Tasks
- 1 Introduction
- 2 Data Preparation and Problem Statement
- 3 Comparison of Learning Processes and the Accuracy of Different Learning Approaches
- 4 Conclusion
- References
- Estimate of the Neural Network Dimension Using Algebraic Topology and Lie Theory
- 1 Motivation
- 2 Related Work
- 2.1 Differential Geometry in Neural Networks
- 2.2 Embedding Dimension of Neural Networks
- 3 The Manifold Assumptions
- 3.1 Smooth Manifolds
- 3.2 Lie Groups
- 4 Persistent Homology
- 4.1 Simplices
- 4.2 Simplicial Complexes
- 4.3 Associated Abelian Groups
- 4.4 Homological Persistence
- 4.5 Persistence Landscapes
- 5 Neural Networks
- 6 Counting Betti Numbers
- 7 Experimental Setting
- 7.1 Persistence Landscapes Hyperparameters
- 7.2 Neural Network Hyperparameters
- 7.3 Invertible Neural Network Architecture
- 7.4 Experimental Results
- 8 Conclusion
- References
- On the Depth of Gestalt Hierarchies in Common Imagery
- 1 Introduction
- 1.1 Related Work on Perceptual Grouping
- 1.2 Related Work on Aggregation of Parts
- 2 Gestalt Algebra
- 2.1 Operations
- 2.2 Search
- 3 Application to Example Imagery
- 3.1 Bottom-Up Analysis of Sections of the Image
- 3.2 Performance Assessment of the Application to a Set of Image Sections
- 3.3 Larger-Scale Gestalten on Global Image Level
- 3.4 Top-Down Constraint Enforcement
- 4 Discussion and Conclusion
- References
- Image Recognition Algorithms Based on the Representation of Classes by Convex Hulls
- 1 Introduction
- 2 The Definition of a Classifier Based on the Convex Hull Representation of Classes
- 3 Determining the Distance from the Test Point to the Convex Hull
- 3.1 Lite Distance Determination Method
- 3.2 A Method Based on Linear Programming
- 4 The Nearest Convex Hull Algorithm Based on the Linear Programming Method
- 5 Experimental Research
- 6 Conclusion
- References
- Tire Surface Segmentation in Infrared Imaging with Convolutional Neural Networks
- 1 Introduction
- 2 Methodology
- 2.1 Building a Dataset with a Heuristic Method
- 2.2 Proposed Architecture
- 2.3 Validation and Optimization
- 3 Experiments and Results
- 4 Conclusions
- References
- Human Action Recognition Using Recurrent Bag-of-Features Pooling
- 1 Introduction
- 2 Proposed Method
- 2.1 Bag-of-Features
- 2.2 Proposed Recurrent BoF
- 3 Experimental Evaluation
- 4 Discussion
- 5 Conclusions
- References
- Algorithms Based on Maximization of the Mutual Information for Measuring Parameters of Canvas Texture from Images
- 1 Introduction
- 2 Algorithms for Counting Threads
- 2.1 Filtering
- 2.2 Thresholding
- 2.3 Thread Counting
- 3 Experiment
- 4 Application of the Proposed Algorithms to Canvas Images of Paintings by F.S. Rokotov
- 5 Conclusions
- References
- Machine Learning Approach for Contactless Photoplethysmographic Measurement Verification
- 1 Introduction
- 2 Materials and Methods
- 2.1 Experimental Setup
- 2.2 Data Processing
- 3 Results
- 4 Conclusions
- References
- On New Kemeny's Medians
- 1 The Classic Kemeny's Median
- 2 The Kemeny's Metric Median
- 3 The Kemeny's Weighted Median
- 4 Weights Searching
- 5 Conclusion
- References
- Image Decomposition Based on Region-Constrained Smoothing
- 1 Introduction
- 2 Filtering Methods Preserving Image Structure
- 3 An Approach to Region-Constrained Smoothing
- 4 Similarity Factor
- 5 Filtering Based on Similarity Factor
- 6 Experiments
- 7 Conclusion
- References
- Machine Learning Based on Minimizing Robust Mean Estimates
- 1 Introduction
- 1.1 Outliers Problem
- 2 The Principle of Minimizing Robust Average Estimates
- 3 Outliers Insensitive Average Estimates
- 3.1 M-Averages
- 3.2 Smoothly Winsorized Averages
- 3.3 Smoothly Truncated Averages
- 4 Illustrative Examples
- 5 Conclusion
- References
- The Use of Machine Learning Methods to Detect Defects in Images of Metal Structures
- 1 Introduction
- 2 Features of Steel Structure Monitoring Tasks
- 3 Recognition of Structural Elements
- 4 Synthesis Detection of Defects in Steel Structures
- 5 Conclusions
- References
- Multiregion Multiscale Image Segmentation with Anisotropic Diffusion
- 1 Introduction
- 2 Anisotropic Diffusion Based Multiregion Multiscale Image Segmentation
- 2.1 Anisotropic Diffusion Filters
- 2.2 Intra-scale Splitting and Inter-scale Linking
- 2.3 Overall Scale Space Segmentation Method
- 3 Experimental Results
- 3.1 MMIS Segmentation Results
- 3.2 Medical Image Segmentation and Comparisons
- 4 Conclusions
- References
- The Test of Covariation Functions of Cylindrical and Circular Images
- 1 Introduction
- 2 Models of Homogeneous Images on a Cylinder and a Circle
- 3 Models of Inhomogeneous Images
- 4 The Test of Covariation Functions of Cylindrical and Circular Images
- 5 Conclusions
- References
- One-Class Classification Criterion Robust to Anomalies in Training Dataset
- 1 Introduction
- 2 Support Vector Data Description
- 3 Modified One-Class Classification Criterion Robust to the Presence of Outliers
- 4 The Differentiable Form of Criterion
- 5 Experimental Studies
- 6 Conclusion
- References
- Recognition of Tomographic Images in the Diagnosis of Stroke
- 1 Introduction
- 2 Related Work
- 3 Material and Method
- 3.1 Data Expansion
- 3.2 Convolutional Neural Network Architecture
- 3.3 Model Prediction Processing
- 4 Results of Experiments
- 5 Conclusion
- References
- Two-Stage Classification Model for Feather Images Identification
- 1 Introduction
- 2 Related Work
- 3 Dataset Construction
- 4 Experiment
- 4.1 Localization
- 4.2 Classes Normalization
- 4.3 Classification
- 4.4 Results
- 5 Conclusion
- References
- An Objective Comparison of Ridge/Valley Detectors by Image Filtering
- 1 Introduction
- 2 Ridge Extraction in Images
- 2.1 Hessian Matrix
- 2.2 Weingarten
- 2.3 Low Pass Filters for Ridge Detection
- 2.4 Oriented Filters
- 3 Experimental Results and Evaluation
- 3.1 Error Quantification and Evaluation Procedure
- 3.2 Synthetic Images Corrupted by Poisson Noise
- 3.3 Synthetic Images Corrupted by Speckle Noise
- 3.4 Synthetic Images Corrupted by Gaussian Noise
- 3.5 Evaluation with Real Images
- 4 Conclusion
- References
- High-Performance Algorithms Application for Retinal Image Segmentation Based on Texture Features
- 1 Introduction
- 2 An Algorithm for Separating a Laser Exposure Zone in the Retinal Image
- 3 Development of a High-Performance Segmentation Algorithm Based on the Use of Texture Features
- 3.1 An Algorithm for Histogram Generation
- 3.2 An Algorithm for Adjacency Matrix Generation
- 3.3 An Algorithm for Computing a Gradient Field
- 3.4 Algorithms for Computing Sum Vectors
- 4 Computing Texture Features
- 5 Experimental Study of the High-Performance Algorithm Acceleration
- 6 Conclusion
- References
- Learning Topology: Bridging Computational Topology and Machine Learning
- 1 Introduction
- 2 Persistence Homology: History and Basic Notions
- 2.1 Basics
- 2.2 History
- 2.3 Persistence Diagrams
- 3 PH-Based Descriptors and Implementations
- 3.1 Implementations
- 4 A Plethora of Applications
- 5 New Trends: PH into ML
- 5.1 Topological Layers
- 6 Conclusions
- References
- Library of Sample Image Instances for the Cutting Path Problem
- 1 Introduction
- 2 General Definition and Statements
- 3 Formation Principles for Specific Groups (Classes) of Image Instances in the Library
- 4 Computing Experiments
- 5 Conclusion
- References
- Interest Points Detection Based on Sign Representations of Digital Images
- 1 Introduction
- 2 Reduced Sign Representations and Their Graphs
- 3 Interest Points as Concentrators of Paths
- 4 Results of Computer Experiments
- 5 Conclusion
- References
- Memory Consumption and Computation Efficiency Improvements of Viola-Jones Object Detection Method for UAVs
- 1 Introduction
- 2 Viola-Jones Object Detection Method
- 2.1 Edge Haar-Like Features
- 3 Experiments
- 3.1 An Inflatable Life Raft PSN-10
- 3.2 An Oil Storage Tank
- 4 Conclusion
- References
- Automation of the Detection of Pathological Changes in the Morphometric Characteristics of the Human Eye Fundus Based on the Data of Optical Coherence Tomography Angiography
- 1 Introduction
- 2 Problem Statement
- 3 A Method for Automating the Detection of Pathological Changes in the Morphometric Characteristics of the Fundus
- 4 Experimental Investigation of the Proposed Method
- 5 Conclusions
- References
- MobileEmotiFace: Efficient Facial Image Representations in Video-Based Emotion Recognition on Mobile Devices
- 1 Introduction
- 2 Proposed Approach
- 3 Experimental Results
- 4 Conclusion
- References
- Basic Models of Descriptive Image Analysis
- 1 Introduction
- 2 Descriptive Image Models and Representations in Image Analysis
- 3 Models Reflecting the General Properties of the Image Recognition and Analysis Process
- 3.1 A Model Based on a Reversible Algebraic Closure
- 3.2 A Model Taking into Account the Equivalence Property of Images of the Same Class
- 3.3 A Model Based on Multiple Image Models and Multiple Classifiers
- 4 Models Characterizing the Architecture and Structure of the Recognition Process
- 4.1 Multilevel Model for Algorithms and Initial Data Combining in Image Recognition
- 4.2 Information Structure for Generating Descriptive Algorithmic Schemes for Image Recognition
- 5 Conclusion
- References
- Evaluation of Spectral Similarity Measures and Dimensionality Reduction Techniques for Hyperspectral Images
- 1 Introduction
- 2 Methods
- 2.1 Dimensionality Reduction Techniques Used in the Study
- 3 Experiments
- 4 Conclusion
- References
- Maximum Similarity Method for Image Mining
- 1 Introduction
- 2 Characterization of the Identification Problem in the Context of Image Mining
- 3 Image Representation by a Random Counts Set
- 4 Maximum Similarity Method
- 5 Conclusions
- References
- First Step Towards Creating a Software Package for Detecting the Dangerous States During Driver Eye Monitoring
- 1 Introduction
- 2 Algorithms for Eye Detection and Systems for Driver Monitoring
- 3 Hardware Analysis for Driver's Eyes Monitoring System
- 4 Collecting and Preparing Data for Training
- 5 Results of the Software Implementation
- 6 Conclusion
- References
- IUC 2020 - The 1st International Workshop on Human and Vehicle Analysis for Intelligent Urban Computing
- Workshop on Human and Vehicle Analysis for Intelligent Urban Computing (IUC)
- Workshop Description
- Organization
- Organization Chairs
- Program Committee
- Unbalanced Optimal Transport in Multi-camera Tracking Applications
- 1 Introduction
- 2 Related Works
- 2.1 Single View Multi-object Tracking
- 2.2 Multi-view Multi-object Tracking
- 3 Proposed Method
- 3.1 Targets Association Across Cameras as an Unbalanced Optimal Transport Problem
- 3.2 Ground Cost Learning for UOT-Based Targets Association Across Cameras
- 4 Experimental Results
- 4.1 Implementations
- 4.2 Benchmarking Performance
- 4.3 Performance Analysis
- 5 Conclusion
- References
- Arithmetic Evaluation System Based on MixNet-YOLOv3 and CRNN Neural Networks
- 1 Introduction
- 2 Related Work
- 3 Overall Architecture
- 3.1 Detection Branch
- 3.2 Recognition Branch
- 4 Experiments
- 4.1 Dataset
- 4.2 Evaluation
- 5 Conclusion
- References
- HSS-GCN: A Hierarchical Spatial Structural Graph Convolutional Network for Vehicle Re-identification
- 1 Introduction
- 2 Related Work
- 2.1 Vehicle Re-ID
- 2.2 GCN and GCN in Vehicle Re-ID
- 3 Methodology
- 3.1 Global Module
- 3.2 GCN Module with Hierarchical Spatial Graph
- 3.3 Joint Optimization of Multiple Losses
- 4 Experiments
- 4.1 Experiment Settings
- 4.2 Experimental Results and Analysis
- 4.3 Ablation Study
- 5 Conclusion
- References
- A Novel Multi-feature Skeleton Representation for 3D Action Recognition
- 1 Introduction
- 2 Related Work
- 3 The Proposed Method
- 3.1 Encoding Process
- 3.2 Important Angles Between Joints
- 4 Experiments and Analysis
- 4.1 Datasets
- 4.2 Implementation Details
- 4.3 Experimental Evaluation
- 5 Conclusions
- References
- R2SN: Refined Semantic Segmentation Network of City Remote Sensing Image
- 1 Introduction
- 1.1 Motivation
- 1.2 Contributions
- 2 Related Work
- 3 Our Approach
- 3.1 Structure
- 3.2 Architecture of Network
- 3.3 Focal Loss
- 3.4 Hinge Loss
- 4 Experiments
- 4.1 Implementation Details
- 4.2 Ablation Experiment
- 4.3 Comparison with Different Loss Functions
- 4.4 Comparison with State-of-the-Art Methods
- 5 Conclusion
- References
- Light-Weight Distilled HRNet for Facial Landmark Detection
- 1 Introduction
- 2 Proposed Method
- 2.1 Light-Weight HRNet
- 2.2 Dual Soft Argmax
- 2.3 Similarity-FeatureMap Knowledge Distillation
- 3 Experiment and Results
- 4 Conclusion
- A Part Localization Results
- References
- DeepFM-Based Taxi Pick-Up Area Recommendation
- 1 Introduction
- 2 Related Work
- 3 Framework
- 4 Method
- 4.1 Score Prediction Based on DeepFM
- 4.2 Important Attribute of Area
- 4.3 Feature Extracting in DeepFM
- 4.4 Taxi Pick-Up Recommendation
- 5 Experiment
- 6 Summary
- References
- IWBDAF 2020 - International Workshop on Biometric Data Analysis and Forensics
- International Workshop on Biometric Data Analysis and Forensics (IWBDA)
- Organization
- General Chairs
- Program Committee
- Blockchain-Based Iris Authentication in Order to Secure IoT Access and Digital Money Spending
- 1 Introduction
- 2 Blockchain
- 2.1 Transaction Validation
- 2.2 Blockchain Attacks
- 2.3 Blockchain and IoT
- 3 Related Work
- 4 Information Fusion of Prime Numbers and Biometrics for Encrypting Coding
- 5 A Smart Contract in Order to Prevent Double Spending
- 5.1 The Smart Contract
- 6 IIF Approach with a Novel or a Generalized Blockchain
- 6.1 Blockchain Enrollment and Wallet Creation
- 6.2 Permissioned Support Blockchain
- 6.3 Authentication
- 7 Analysis
- 7.1 Security of the Hybrid Key
- 7.2 Privacy
- 8 Conclusions and Future Work
- References
- DeepFakes Evolution: Analysis of Facial Regions and Fake Detection Performance
- 1 Introduction
- 2 Proposed Evaluation Framework
- 2.1 Facial Region Segmentation
- 2.2 Fake Detection Systems
- 3 Databases
- 3.1 UADFV
- 3.2 FaceForensics++
- 3.3 Celeb-DF
- 3.4 DFDC
- 4 Experimental Protocol
- 5 Experimental Results
- 5.1 Entire Face Analysis
- 5.2 Facial Regions Analysis
- 5.3 Comparison with the State of the Art
- 6 Conclusions
- References
- Large Scale Graph Based Network Forensics Analysis
- 1 Introduction
- 1.1 Organization of the Paper
- 2 Related Work
- 3 The Algorithm by Wang and Daniels
- 3.1 Global Reasoning
- 4 Our Algorithm
- 4.1 The MapReduce Paradigm
- 4.2 Apache Spark
- 4.3 Our MapReduce Version of the Algorithm by Wang and Daniels
- 5 Experimental Evaluation
- 5.1 Dataset
- 5.2 Hardware
- 5.3 Results
- 6 Conclusions
- References
- Deep Iris Compression
- 1 Introduction
- 2 Related Work
- 3 Deep Compression Model
- 4 Experimental Framework
- 5 Experiments and Analysis
- 6 Conclusion
- References
- IFEPE: On the Impact of Facial Expression in Head Pose Estimation
- 1 Introduction
- 1.1 Head Pose Estimation
- 1.2 Facial Expression Recognition
- 2 Methods and Materials
- 2.1 HP2IFS for Head Pose Estimation
- 2.2 FMPN-FER for Facial Expression Recognition
- 2.3 Datasets
- 3 Experiments and Results
- 4 Conclusions
- References
- Analysing and Exploiting Complexity Information in On-Line Signature Verification
- 1 Introduction
- 2 Proposed Approach
- 2.1 Signature Complexity Detector
- 2.2 On-Line Signature Verification System
- 3 Database
- 4 Experimental Protocol
- 5 Experimental Work
- 5.1 Exp. 1 - Analysis of Complexity for Baseline Systems
- 5.2 Exp. 2 - Training from Scratch 3 Systems, One System per Complexity
- 5.3 Exp. 3 - Training from Scratch and Changing the Baseline Architecture
- 5.4 Exp. 4 - Fine Tuning 3 Systems
- 5.5 Exp. 5 - Training a Global System with Balanced Classes
- 6 Conclusions and Future Work
- References
- A Novel Ensemble Framework for Face Search
- 1 Introduction
- 2 Related Works
- 2.1 Face Detection and Alignment
- 2.2 Face Feature Extraction
- 2.3 Approximate Nearest Neighbor Search (ANNS)
- 3 Proposed Framework
- 3.1 Face Detection and Alignment
- 3.2 Feature Extraction
- 3.3 Face Search
- 3.4 Fine Matching
- 4 Experiments and Results
- 5 Conclusion
- References
- Real-Time Thermal Face Identification System for Low Memory Vision Applications Using CNN
- 1 Introduction
- 2 Materials and Data
- 2.1 Thermal Camera
- 2.2 Microcontroller
- 2.3 Datasets
- 3 Related Works
- 4 Proposed CNN Architecture
- 5 Algorithm Pipeline
- 6 Experimental Analysis and Results
- 7 Conclusion
- References
- MADiMa 2020 - 6th International Workshop on Multimedia Assisted Dietary Management
- Preface
- Organization
- Workshop Chairs
- Publication Chair
- Program Committee
- Additional Reviewer
- Assessing Individual Dietary Intake in Food Sharing Scenarios with Food and Human Pose Detection
- 1 Introduction
- 2 Related Work
- 3 Method
- 3.1 Dish Detection
- 3.2 Human Pose Estimation
- 3.3 Eating State Estimation
- 3.4 Bite Counting
- 4 Experiments
- 4.1 Dataset
- 4.2 Results
- 5 Conclusion
- References
- Recognition of Food-Texture Attributes Using an In-Ear Microphone
- 1 Introduction
- 2 Attribute Recognition Algorithms
- 2.1 Chew-Level Algorithm
- 2.2 Chewing-Bout-Level Algorithm
- 3 Data-Set and Evaluation Metrics
- 4 Evaluation and Results
- 5 Conclusions
- References
- Visual Aware Hierarchy Based Food Recognition
- 1 Introduction
- 2 Related Work
- 2.1 Image-Based Dietary Assessment
- 2.2 Food Detection and Food Localization
- 2.3 Food Image Recognition
- 2.4 Food Image Datasets
- 3 VIPER-FoodNet (VFN) Dataset
- 3.1 Food Categories
- 3.2 Semi-automatic Food Image Collection and Annotation
- 4 Food Recognition System
- 4.1 Food Localization
- 4.2 Food Classification
- 5 Experimental Results
- 5.1 Food Localization
- 5.2 Food Classification
- 5.3 Food Recognition
- 6 Discussion
- 7 Conclusion
- References
- Analysis of Chewing Signals Based on Chewing Detection Using Proximity Sensor for Diet Monitoring
- 1 Introduction
- 2 Hardware Design
- 3 Methodology
- 3.1 Data Collection
- 3.2 Chewing Detection
- 3.3 Chewing Analysis
- 4 Results
- 4.1 Chewing Detection
- 4.2 Chew Count Estimation
- 5 Discussions
- 6 Conclusion
- References
- Food Recognition in the Presence of Label Noise
- 1 Introduction
- 2 Related Work
- 2.1 Food Recognition
- 2.2 Noisy Labels
- 3 Method
- 3.1 Confusion Matrix (CM) Building
- 3.2 Noise Layer
- 4 Experimental Results
- 4.1 Dataset
- 4.2 Evaluation Metrics
- 4.3 Results
- 5 Conclusions
- References
- S2ML-TL Framework for Multi-label Food Recognition
- 1 Introduction
- 2 Related Works
- 3 Proposed Methodology
- 3.1 S2ML-TL Framework
- 3.2 Class Priors for Improved Transferability of Food Recognition
- 4 Validation
- 4.1 Datasets
- 4.2 Evaluation Metrics
- 4.3 Implementation Details
- 4.4 Results and Discussion
- 4.5 Ablation Study
- 5 Conclusions
- References
- UEC-FoodPix Complete: A Large-Scale Food Image Segmentation Dataset
- 1 Introduction
- 2 Related Work
- 3 Dataset Construction
- 4 Evaluation
- 5 Application 1: Region-Based Food Calorie Estimation
- 5.1 Method
- 5.2 Experimental Results
- 6 Application 2: Mask-Based Image Synthesis
- 7 Conclusions
- References
- Event Mining Driven Context-Aware Personal Food Preference Modelling
- 1 Introduction
- 2 Related Research
- 3 Food Event Model
- 3.1 The Causal Aspect
- 4 Food Preference Space: Taste Space
- 5 Experimental Design
- 6 Results
- 6.1 RQ1: Contextual Variation in Taste Profile
- 6.2 RQ2: Comparison of Prediction Performance
- 6.3 RQ3: Model Accuracy with Training Data Volume
- 7 Conclusion and Future Work
- References
- Analysis of Traditional Italian Food Recipes: Experiments and Results
- 1 Introduction
- 2 Related Works
- 3 Recipe Analysis
- 4 Recipe Visualization Application
- 5 CookIt Portal
- 6 Future Works and Conclusions
- References
- Author Index
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