Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications

Name: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications | 21st Iberoamerican Congress, CIARP 2016, Lima, Peru, November 8-11, 2016, Proceedings
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21st Iberoamerican Congress, CIARP 2016, Lima, Peru, November 8-11, 2016, Proceedings

César Beltrán-Castañón Ingela Nyström Fazel Famili(Herausgeber*in)

Springer (Verlag)

Erschienen am 14. Februar 2017

XVIII, 541 Seiten

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978-3-319-52277-7 (ISBN)

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Inhalt

Intro
Preface
Organization
Contents
Direction-Based Segmentation of Retinal Blood Vessels
Abstract
1 Introduction
2 Building the Direction Map DMG
3 The Segmentation Method
4 Experimental Results and Concluding Remarks
References
Identifying Aedes aegypti Mosquitoes by Sensors and One-Class Classifiers
1 Introduction
2 Optical Sensor and Insect Data
2.1 Data Collection
2.2 Feature Extraction
3 One-Class Classification
4 Experimental Evaluation
5 Conclusion
References
Partial Matching of Finger Vein Patterns Based on Point Sets Alignment and Directional Information
Abstract
1 Introduction
2 The Proposed Approach
3 Experiments and Results
4 Conclusion
References
Highly Transparent and Secure Scheme for Concealing Text Within Audio
1 Introduction
2 Proposed Audio Steganography Model
2.1 Embedding Module
2.2 Recovering Module
3 Experimental Results and Discussion
3.1 Transparency
3.2 Security
4 Conclusion
References
Spatio-Colour Asplünd's Metric and Logarithmic Image Processing for Colour Images (LIPC)
1 Introduction
2 Prerequisites
2.1 LIPC Model
2.2 Marginal Asplünd's Metric for Colour and Multivariate Images
3 Asplünd's Metric Defined in the Logarithmic Image Processing Colour (LIPC) Framework
4 Examples
5 Conclusion and Perspectives
References
Two Compound Random Field Texture Models
1 Introduction
2 Compound Random Field Texture Models
2.1 Region Switching Model
2.2 Local Markov Models
3 Experiments
4 Conclusion
References
An Automatic Tortoise Specimen Recognition
1 Introduction
2 Discriminative Tortoise Features
3 Automatic Detection of Tortoise Features
3.1 Plastron Localization
3.2 Central Seam Junctions Localization
4 Tortoise Classification
5 Experimental Results
5.1 Feature Discriminability Validation
5.2 Classification of Automatically Measured Features
6 Conclusion
References
Autonomous Scanning of Structural Elements in Buildings
Abstract
1 Introduction: Key Points and Contributions
2 A Brief Overview of the Method
3 Structural Elements Recognition
3.1 Finding the Region of Interest
3.2 Structural Elements Classification
4 NBS
5 Test and Experimental Comparison
6 Conclusions
Acknowledgements
References
Parallel Integer Motion Estimation for High Efficiency Video Coding (HEVC) Using OpenCL
1 Introduction
2 Parallel Integer Motion Estimation
2.1 Distortion Measure Calculations
2.2 Distortion Measure Accumulations
2.3 Estimating Minima of Rate-Distortion
2.4 GPU and CPU Communication
3 Experimental Evaluation
3.1 Experimental Setup and Encoder Configuration
3.2 Experimental Results
4 Conclusions
References
Automatic Fruit and Vegetable Recognition Based on CENTRIST and Color Representation
1 Introduction
2 Background
2.1 CENTRIST
2.2 Color CENTRIST
3 Methodology
3.1 Preprocessing
3.2 Feature Extraction
3.3 Feature Reduction and Classification
4 Experimental Results
5 Conclusions
References
Scale Sensitivity of Textural Features
1 Introduction
2 Textural Features
2.1 2DCAR Illumination Invariant Features
2.2 Local Binary Patterns
2.3 Gabor Features
2.4 Histogram Based Features
3 Experiments
4 Conclusion
References
Noise-Added Texture Analysis
1 Introduction
2 Regionalized Variables in an Image
3 Measuring Dissimilarity of Regionalized Variables
4 Experiments
5 Conclusion
References
Breast Density Classification with Convolutional Neural Networks
1 Introduction
1.1 Breast Density
1.2 American College of Radiology: BIRADS Categories
1.3 Radiologist Agreement and Performance Evaluation
2 The Breast Density Dataset
3 Methods
3.1 HT-L3 Visual Features with Random Filters
3.2 Deep Learning Trained with the Image.net and Fine-Tuned with the Breast Density Dataset
4 Results
5 Conclusions
References
Community Feature Selection for Anomaly Detection in Attributed Graphs
1 Introduction
2 Related Work
3 Basic Concepts
4 Improving Anomaly Detection Using Community Features
5 Experimental Results
6 Conclusions
References
Lung Nodule Classification Based on Deep Convolutional Neural Networks
1 Introduction
2 Background
2.1 Lung Nodule Classification
2.2 Deep Learning
3 Proposed Method
3.1 Preprocessing and Data Augmentation
3.2 Architecture
3.3 Learning
3.4 Adjacent Rejection
4 Experimental Results
4.1 Dataset
4.2 Results
5 Conclusions
References
A Hierarchical K-Nearest Neighbor Approach for Volume of Tissue Activated Estimation
1 Introduction
2 Materials and Methods
3 Experimental Set-Up
4 Results and Discussion
5 Conclusions
References
Discriminative Capacity and Phonetic Information of Bottleneck Features in Speech
1 Introduction
2 Bottleneck Features
3 Discriminative Capacity of the BN Features
4 Phonetic Information Conveyed by the BN Features
5 Experimental Setup
5.1 Data Corpus
5.2 The DNN Toolkit
5.3 Experiments
6 Results
7 Conclusions
References
Boosting SpLSA for Text Classification
1 Introduction
2 Related Work
3 Supervised pLSA and Our Extensions
3.1 Variables and Assumptions
3.2 Supervised pLSA (spLSA)
3.3 Model Fitting
3.4 Label Inference on New Documents
3.5 A First Extension: SpLSA Regularization
3.6 A Second Extension: Modeling Label Uncertainty
4 Experiments
4.1 Data Sets
4.2 Results
5 Conclusions
References
A Compact Representation of Multiscale Dissimilarity Data by Prototype Selection
1 Introduction
2 Proposed Method
3 Experimental Analysis
4 Conclusions
References
A Kernel-Based Approach for DBS Parameter Estimation
1 Introduction
2 Materials and Methods
3 Experimental Set-Up
4 Results and Discussion
5 Conclusions
References
Consensual Iris Segmentation Fusion
1 Introduction
2 Iris Consensual Segmentation Fusion by Segmentation Ensemble via Kernels
3 Experimental Design
3.1 Results and Discussion
4 Conclusions
References
Depth Estimation with Light Field and Photometric Stereo Data Using Energy Minimization
1 Introduction
2 Acquisition Setup
3 Combination of Light Fields and Photometric Stereo
3.1 Light Field Depth Estimation
3.2 Surface Normals from Photometric Stereo
3.3 Energy Minimization
4 Experimental Results
5 Summary and Outlook
References
Distributed and Parallel Algorithm for Computing Betweenness Centrality
1 Introduction
2 Background
3 Our Proposal
3.1 Modification for Sparse Networks
3.2 Analysis
4 Experiments
5 Conclusions and Future Work
References
A New Parallel Training Algorithm for Optimum-Path Forest-Based Learning
1 Introduction
2 Supervised Classification Based on Optimum-Path Forest
2.1 Training
2.2 Testing
3 Parallel-Driven Optimum-Path Forest Training
4 Experiments and Results
5 Conclusions and Future Work
References
Face Composite Sketch Recognition by BoVW-Based Discriminative Representations
1 Introduction
2 Proposal: BoVW-Based Discriminative Representation
3 Experimental Analysis
4 Conclusions
References
Efficient Sparse Approximation of Support Vector Machines Solving a Kernel Lasso
1 Introduction
2 Problem Statement and Related Work
3 Sparse SVM Approximations via Kernelized Lasso
4 Experimental Results
5 Conclusions
References
Metric Learning in the Dissimilarity Space to Improve Low-Resolution Face Recognition
1 Introduction
2 Related Work
3 Proposed Approach: Dissimilarity Space and Metric Learning for LRFR
3.1 Dissimilarity Space
3.2 Metric Learning Approach
4 Experimental Evaluation
4.1 Experiments and Discussion on SCFace Database
4.2 Experiments and Discussion on LFW Database
5 Conclusions
References
Video Temporal Segmentation Based on Color Histograms and Cross-Correlation
1 Introduction
2 Background
3 Methodology
3.1 Histogram-Based Dissimilarity
3.2 Block-Based Cross-Correlation
3.3 Fusion
3.4 Adaptive Thresholding
4 Experimental Results
5 Conclusions and Future Work
References
Automatic Classification of Herbal Substances Enhanced with an Entropy Criterion
1 Introduction
2 Data Preprocessing
3 Discovery of Classes
4 Entropy-Based Template Selection
5 SVM Classification
6 Experimental Results and Discussion
7 Conclusions and Future Work
References
Extended LBP Operator to Characterize Event-Address Representation Connectivity
1 Introduction
2 Features Generation
2.1 Dynamic Vision Sensor Data
2.2 Events Orientation
2.3 Events Connectivity
3 Grouping Features as Histograms
4 Discussions and Conclusions
References
Definition and Composition of Motor Primitives Using Latent Force Models and Hidden Markov Models
1 Introduction
2 Materials and Methods
2.1 Latent Force Models
2.2 Hidden Markov Models
2.3 HMM and LFM
2.4 Learning the Model
3 Experimental Results
3.1 Synthetic Data
3.2 Real Data
4 Conclusions
References
Similarity Measure for Cell Membrane Fusion Proteins Identification
1 Introduction
2 Background
3 Proposed System
3.1 Development of a Similarity Measure
3.2 Classification
4 Data Description and Experimental Results
4.1 Data Pre-processing
5 Conclusions and Future Work
References
Abnormal Behavior Detection in Crowded Scenes Based on Optical Flow Connected Components
1 Introduction
2 Proposed Method
2.1 OFCCs Computation
2.2 Normal Behavior Model
2.3 Abnormality Detection
3 Results and Comparisons
4 Conclusions
References
Identifying Colombian Bird Species from Audio Recordings
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Feature Extraction and Audio Representation
2.3 Automatic Identification of Bird Species
2.4 Visualization of Bird Species
3 Experiments and Results
3.1 Classification Experiments
3.2 Visualization Experiments
4 Conclusion and Future Work
References
GMM Background Modeling Using Divergence-Based Weight Updating
1 Introduction
2 Methods
3 Experimental Set-Up
4 Results and Discussion
5 Conclusions
References
Bayesian Optimization for Fitting 3D Morphable Models of Brain Structures
1 Introduction
2 Materials and Methods
2.1 Database
2.2 3D Brain Model
2.3 Bayesian Optimization with Gaussian Process Priors
2.4 Morphable Model Fitting Using Bayesian Optimization
3 Results and Discussions
3.1 Training Results for 3D-MM
3.2 Fitting Results Using Bayesian Optimization
4 Conclusions and Future Works
References
Star: A Contextual Description of Superpixels for Remote Sensing Image Classification
1 Introduction
2 Star Descriptor
2.1 Segmentation into Superpixels
2.2 Graph Modeling
2.3 Vertex Descriptors
2.4 Edge Descriptors
2.5 Final Descriptor Composition
3 Experimental Protocol
4 Results
5 Conclusion
References
A Similarity Indicator for Differentiating Kinematic Performance Between Qualified Tennis Players
1 Introduction
2 Kernel Based Multi-channel Data Representation
3 Performance Comparison Expanded to RKHS Representation
4 Experimental Setup and Results
4.1 Database
4.2 Baseline Kinematic Analysis
4.3 Kernel-Based Performance Analysis
5 Discussion and Concluding Remarks
References
Subsampling the Concurrent AdaBoost Algorithm: An Efficient Approach for Large Datasets
1 Introduction
2 Adaptive Boosting and Some Parallel Variants
3 Subsampling the Concurrent AdaBoost Algorithm
4 Experimentation
5 Conclusions
References
Deep Learning Features for Wireless Capsule Endoscopy Analysis
1 Introduction
2 Frame-Based Motility Events
3 Feature Learning Using Convolution Neural Networks
3.1 Our Network Architecture
3.2 CNN Training
4 Experimental Results
4.1 Quantitative Results
4.2 Qualitative Results
5 Conclusions
References
Interactive Data Visualization Using Dimensionality Reduction and Similarity-Based Representations
1 Introduction
2 Data Visualization via Dimensionality Reduction
3 Interactive Data Visualization Scheme
3.1 Mixture
3.2 Interaction Model
3.3 Similarity-Based Visualization
4 Experimental Setup
5 Results and Discussion
6 Conclusions and Future Work
References
Multi-labeler Classification Using Kernel Representations and Mixture of Classifiers
1 Introduction
2 Related Works and Background
3 Proposed Multi-labeler Classification Approach
3.1 Modified Supervised Kernel
3.2 Multi-labeler Approach
3.3 Estimation of Weighting Factors
4 Results and Discussion
5 Conclusions and Future Work
References
Detection of Follicles in Ultrasound Videos of Bovine Ovaries
1 Introduction
2 Dataset
3 Signal Processing for Follicle Detection
3.1 Follicle-Like Regions Detection in Each Frame
3.2 Temporal Coherence by Multiple Tracking
3.3 Identification of the Ovarian Region
3.4 Follicle Identification and Measurement
4 Experiments and Results
5 Concluding Remarks
References
Decision Level Fusion for Audio-Visual Speech Recognition in Noisy Conditions
1 Introduction
2 Proposed Approach
3 Audio-Visual Databases
4 Experimental Results
5 Conclusions
References
Improving Nearest Neighbor Based Multi-target Prediction Through Metric Learning
1 Introduction
2 General Notation and State of the Art
3 Distance Metric Learning for Multi-target Prediction (DMLMTP)
4 Experiments
5 Concluding Remarks and Further Work
References
An Approximate Support Vector Machines Solver with Budget Control
1 Introduction
2 Proposal
2.1 Sparsity Constraints
3 Experiments
3.1 Experimental Setup
3.2 Discussion
4 Conclusion
References
Multi-biometric Template Protection on Smartphones: An Approach Based on Binarized Statistical Features and Bloom Filters
1 Introduction
2 Proposed Multi-biometric Approach
2.1 Face and Periocular Segmentation
2.2 Generalized Feature Extraction and Binarization
2.3 Biometric Template Protection: Bloom Filters
3 Experimental Setup and Results
3.1 Real-Time Evaluation of the Proposed System
4 Conclusion
References
Computing Arithmetic Operations on Sequences of Handwritten Digits
1 Introduction
2 Previous Work
3 Handwritten Arithmetics with Deep Learning
3.1 Problem Description
3.2 Deep Learning Architecture
4 Experiments and Results
4.1 Dataset and Sequences
4.2 Training
4.3 Testing
5 Conclusions and Future Work
References
Automatic Classification of Non-informative Frames in Colonoscopy Videos Using Texture Analysis
1 Introduction
2 Automatic Classification of Non-Infomative Frames
2.1 Frequency Domain Transform
2.2 Texture Analysis
2.3 Classification Using Support Vector Machines
3 Experimental Evaluation
3.1 Evaluation Conditions
3.2 Results and Discussion
4 Final Remarks
References
Efficient Training Over Long Short-Term Memory Networks for Wind Speed Forecasting
1 Introduction
2 Long Short-Term Memory
3 An Efficient Training for LSTM
4 Experiments and Results
5 Conclusions and Future Work
References
Classifying Estimated Stereo Correspondences Based on Delaunay Triangulation
1 Introduction
2 Corresponding Points Classification
2.1 Fundamentals
2.2 Classification Based on Delaunay Triangulation
3 Experimental Evaluation
4 Conclusions
References
Data Fusion from Multiple Stations for Estimation of PM2.5 in Specific Geographical Location
Abstract
1 Introduction
2 Materials and Methods
2.1 Database
2.2 Theoretical Background
3 Results and Discussion
4 Conclusions
Acknowledgments
References
Multivariate Functional Network Connectivity for Disorders of Consciousness
1 Introduction
2 Materials and Methods
2.1 Participants and Data Acquisitions
2.2 fMRI Preprocessing
2.3 Community Detection
2.4 Multivariate FNC Method
2.5 Group Analysis
3 Results
4 Conclusions
References
Non-parametric Source Reconstruction via Kernel Temporal Enhancement for EEG Data
1 Introduction
2 Materials and Methods
2.1 Inverse Problem
2.2 LORETA
2.3 Kernel Temporal Enhancement
2.4 Reconstruction Error Metrics
2.5 Experimental Setup
3 Results
4 Discussion and Conclusions
References
Tsallis Entropy Extraction for Mammographic Region Classification
1 Introduction
2 Related Works
3 Methodology
3.1 Gray-Level Co-occurrence Matrix (GLCM)
3.2 Multilevel Decomposition
3.3 Weighted Haralick Features
3.4 Tsallis Entropy
3.5 Classification
4 Database Acquisition
4.1 ROI Extraction
5 Experiments
5.1 Experiment I: Fixed Direction and q [0.1, 1.9]
5.2 Experiment II: Two Refined Ranges: [1.31, 1.39] and [1.41, 1.49]
6 Conclusions and Future Works
References
Edge Detection Robust to Intensity Inhomogeneity: A 7T MRI Case Study
1 Introduction
2 Related Works
2.1 Parameter Selection
2.2 Edge Refining
3 Proposed Methodology
4 Experiments
5 Conclusion
References
Fine-Tuning Based Deep Convolutional Networks for Lepidopterous Genus Recognition
1 Introduction
2 Related Work
3 Proposed Approach
4 Experimental Results
5 Conclusions
References
Selection of Statistically Representative Subset from a Large Data Set
Abstract
1 Introduction
1.1 Related Works
1.2 Problem Setting
2 Testing Complex Hypotheses
2.1 Testing Hypothesis in Hard and Soft Modes
2.2 Null-Hypothesis and Artificial Contrary Hypothesis
3 Method
3.1 Steps of Algorithm
3.2 Evaluation of Results
4 Experiments
4.1 Selecting Companies of Mobile Communication (Russia)
4.2 Selecting Modes of Movements in Intercity Autobus Communication (Peru)
5 Conclusions
References
Non-local Exposure Fusion
1 Introduction and Previous Works
2 Non-local Exposure Fusion
2.1 Classical Exposure Fusion
2.2 Non-local Fusion
2.3 Computing Pixel Similarity
2.4 Algorithm Details
3 Experiments
4 Conclusions
References
Analysis of the Geometry and Electric Properties of Brain Tissue in Simulation Models for Deep Brain Stimulation
1 Introduction
2 Materials and Methods
2.1 Simulation Models for DBS and Geometries
2.2 Brain Conductivity Through Diffusion Magnetic Resonance Imaging (dMRI)
3 Experimental Results
3.1 Anisotropy Level of Brain Structures for Each Patient
3.2 Simulations of DBS Models
3.3 Discussion
4 Conclusions and Future Work
References
Spatial Resolution Enhancement in Ultrasound Images from Multiple Annotators Knowledge
1 Introduction
2 Materials and Methods
2.1 Dataset
2.2 Spatial Resolution Enhancement Based on Gaussian Processes Regression with Multiple Annotators
2.3 Procedure
3 Results and Discussions
4 Conclusion
References
How Deep Can We Rely on Emotion Recognition
1 Introduction
2 Related Work
3 Proposed Emotion Recognition Model
4 Experimental Design
5 Results and Discussion
6 Conclusion
References
Sparse Linear Models Applied to Power Quality Disturbance Classification
1 Introduction
2 Materials and Methods
2.1 Power Quality (PQ) Disturbances
2.2 Overcomplete Representation
2.3 Sparse Linear Models for Grouped Variable Selection
2.4 Procedure
3 Results and Discussions
4 Conclusions
References
Trading off Distance Metrics vs Accuracy in Incremental Learning Algorithms
1 Introduction
2 Incremental Hypersphere Classifier (IHC) Algorithm
3 Experimental Results
4 Conclusions and Future Work
References
Author Index

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