Pattern Recognition: Applications and Methods

Name: Pattern Recognition: Applications and Methods | 4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers
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4th International Conference, ICPRAM 2015, Lisbon, Portugal, January 10-12, 2015, Revised Selected Papers

Ana Fred Maria De Marsico Mário Figueiredo(Editor)

Springer (Publisher)

Published on 8. January 2016

XVI, 301 pages

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978-3-319-27677-9 (ISBN)

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Content

Intro
Preface
Organization
Contents
Invited Paper
3D Computer Vision: From Points to Concepts
1 Introduction
2 3D Sensors
3 Keypoints
4 Descriptors
4.1 Evaluating Descriptors
4.2 Genetic Algorithm-Evolved 3D Point Cloud Descriptor
5 3D Object Recognition
5.1 Set Distances
5.2 Deep Transfer Learning for 3D Object Recognition
6 3D Object Tracking
7 Challenges
8 Conclusion
References
Theory and Methods
Density Difference Detection with Application to Exploratory Visualization
1 Introduction
2 Theoretical Foundations
2.1 Scale Space Representation
2.2 Kernel Density Estimation
2.3 Bandwidth Selection
2.4 Multiple Groups
3 Detection Framework
3.1 Scale Tracing
3.2 Spot Detection
3.3 Shape Adaption
4 Exploratory Visualization
4.1 Star Coordinate Visualization
4.2 Preserving Orthography
4.3 Guiding Explorations
5 Experiments
5.1 Decision Rule
5.2 Data Sets
5.3 Parameter Investigation
5.4 Classification Results
6 Conclusion
References
Identifying and Mitigating Labelling Errors in Active Learning
1 Introduction
2 Background
2.1 Active Learning with Uncertainty
2.2 Impact of Label Noise
3 Characterizing Mislabelled Instances
3.1 Mislabelling Likelihood
3.2 Informativeness of Possibly Mislabelled Instances
4 Mitigating Label Noise
4.1 Discard, Weight and Relabel
5 Experiments
5.1 Mislabelling Likelihood
5.2 Label Noise Mitigation
6 Conclusion and Future Work
References
A Holistic Classification Optimization Framework with Feature Selection, Preprocessing, Manifold Learning and Classifiers
1 Introduction
2 Automatic Optimization Frameworks
3 Classification Pipeline
3.1 Feature Selection Element
3.2 Feature Preprocessing Element
3.3 Feature Transform Element
3.4 Classifier Element
3.5 Hyperparameters
4 Optimization of the Pipeline Configuration
4.1 Extended Evolution Strategies
4.2 Optimization Target Function
4.3 Multi-pipeline Classifier
5 Experiments
5.1 Evaluation of the Optimization Process
5.2 Analysis of the Optimization Trajectory
5.3 Top Configuration Graph
5.4 Evaluation of the Generalization
6 Conclusions
References
Feature Extraction and Learning Using Context Cue and R00E9nyi Entropy Based Mutual Information
Abstract
1 Introduction
2 Feature Extraction Using CKD
2.1 Formulation of CMK
2.2 Approximation of CMK
3 Feature Learning Using CSQMI
3.1 R00E9nyi Entropy and CSQMI
3.2 Codebook Selection and Refinement Using CSQMI
3.2.1 Codebook Selection
3.2.2 Codebook Refinement
4 Experiments
4.1 Parameter Configuration
4.2 Evaluation of Codebook Learning
4.3 Evaluation of Object Recognition
4.4 Evaluation of Object Detection
5 Conclusion
Acknowledgements
References
Detection of Abrupt Changes in Spatial Relationships in Video Sequences
1 Introduction
2 Rupture Detection Approach
2.1 Fuzzy Object Representation
2.2 Spatial Relationships and Rupture Detection
3 Experiments and Evaluations
3.1 Parameters Tuning
3.2 Ruptures in Spatial Relationships
3.3 Impact of Object Representation
4 Conclusion
References
Diffusion-Based Similarity for Image Analysis
1 Introduction
2 Diffusion Distance and Clustering
3 The Problems of Diffusion Distance
4 Normalised Diffusion Cosine Similarity
5 Experimental Results
6 Conclusions
References
Automatic Detection and Recognition of Symbols and Text on the Road Surface
1 Introduction
2 Related Work
3 Detection and Sorting of Candidate Regions
3.1 Detection of Candidate Regions
3.2 Sorting of Candidates into Words and Symbols
4 Recognition of Words
4.1 Correction of Perspective Distortion of Words
4.2 OCR of Region
5 Recognition of Symbols
5.1 Selection of Classifier
5.2 Selection of HOG Block Density
6 Temporal Information
6.1 Calculation of Road Movement
6.2 Matching and Temporal Fusion of Words and Symbols
7 Results
7.1 Results for Text Detection and Recognition
7.2 Results for Symbol Detection and Recognition
7.3 Failure Cases
8 Conclusion
References
Applications
Using BLSTM for Spotting Regular Expressions in Handwritten Documents
1 Introduction
2 Related Work
3 BLSTM-CTC/HMM System
3.1 Character Recognition and Segmentation
3.2 Handwritten Word Spotting Model
3.3 Regular Expression Spotting Model
4 Experiments
4.1 Features Set
4.2 Results and Discussion
4.3 Using the BLSTM Without HMM
5 Conclusion
References
A Similarity-Based Color Descriptor for Face Detection
1 Introduction
2 Three-Patch LBP Descriptor and a Multi Scale Variant
3 A New Color Descriptor - Coupled-Chroma TPLBP
4 Evaluation of Color Descriptors
4.1 Invariance to Photometric and Geometric Variations
4.2 Invariance to Gaussian Noise
4.3 Discriminative Power
5 Evaluation of Color Descriptors in a Face Detection Setting
5.1 Dataset
5.2 Evaluation Protocol
5.3 Results
6 Conclusions
References
Pose Estimation and Movement Detection for Mobility Assessment of Elderly People in an Ambient Assisted Living Application
1 Introduction
2 Related Work
3 Mobility Assessment
3.1 Person Localisation
3.2 Movement Detection
3.3 Pose Estimation
3.4 Human Machine Interface
4 Experimental Results
5 Action Recognition
6 Conclusions
7 Future Work
References
A Non-rigid Face Tracking Method for Wide Rotation Using Synthetic Data
1 Introduction
2 Face Representation
2.1 Shape Representation
2.2 Projection
2.3 Appearance Representation
3 Our Method
3.1 Model Training from Synthesized Data
3.2 Robust Initialization
3.3 Matching Strategy by Keyframes
3.4 Fitting via Pose-Wise Classifiers
4 Experimental Results
5 Conclusions
References
3-D Face Recognition Using Geodesic-Map Representation and Statistical Shape Modelling
1 Introduction
2 Sparse Facial Landmark Detection
3 Geodesic-Map Representation
4 Geodesic-Map Matching
5 Dimensionality Reduction
6 New Dataset Fitting
7 Experimental Results
7.1 Facial Expression Changes
7.2 Data Resolution Variation
7.3 Missing Data
8 Conclusions
References
Learning Discriminative Mid-Level Patches for Fast Scene Classification
1 Introduction
2 Related Work
3 Discovering Discriminative Patches: Designed for Speed
3.1 Patch Selection and Feature Extraction
3.2 Classifier Training
3.3 Classifier Selection
4 Image Representation and Scene Classification
5 Experiments and Results
6 Conclusion
References
Modification of Polyp Size and Shape from Two Endoscope Images Using RBF Neural Network
1 Introduction
2 VBW Model
3 Proposed Approach
3.1 Estimating Reflectance Parameter
3.2 NN Learning for Modification of Surface Gradient
3.3 NN Generalization and Modification of Z
3.4 Regression Analysis for Shape Modification
4 Experimental Results
4.1 NN Learning
4.2 Order Number in Polynomial with Regression Analysis
4.3 Computer Simulation
4.4 Real Image Experiments
5 Conclusion
References
Detecting and Dismantling Composite Visualizations in the Scientific Literature
1 Introduction
2 Related Work
3 Decomposition Algorithm
3.1 Step 1: Splitting
3.2 Step 2: Merging
3.3 Step 3: Selecting
4 Composite Figure Detection
5 Experimental Evaluation
6 Limitations and Future Work
7 Conclusions
References
Tensor Deep Stacking Networks and Kernel Deep Convex Networks for Annotating Natural Scene Images
1 Introduction
2 Convex Deep Learning Models
2.1 Tensor Deep Stacking Networks
2.2 Kernel Deep Convex Networks
2.3 Framework for Image Annotation
3 Experiments and Results
3.1 Experimental Setup
3.2 Feature Extraction
3.3 Datasets Used
3.4 Results
4 Summary and Conclusions
References
MOSAIC: Multi-object Segmentation for Assisted Image ReConstruction
1 Introduction
2 MOSAIC Procedures
2.1 Fragment Catalogue
2.2 Fragment Search
3 MOSAIC Interface
4 Experimental Results
4.1 An Experiment on a Real Life Case
5 Conclusions
References
Author Index

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Pattern Recognition: Applications and Methods

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