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Details
Table of Contents
Intro
Foreword
Preface
Contents
About the Editors
Part I Vision-Based Technologies for Accessible Human Computer Interfaces
A Framework for Gaze-Contingent Interfaces
1 Introduction
1.1 Gaze-Contingent Interface
1.2 Eye Tracking and Gaze Detection
1.3 Gaze-Contingent Interface Based on Near Infrared Camera of Mobile Device
2 Methods
2.1 Framework
2.2 Calibration and Standard Acquisition
2.3 Determination of Sagittal Plane
2.4 Calculation of POG with Head Adjustment
2.5 Gaze Prediction by LSTM
2.6 Measurement of Head and Eye Movements
3 Use Cases
3.1 Use Case #1: Select an Option on Screen
3.2 Use Case #2: Auto Screen Scrolling
4 Future Work
References
Sign Language Recognition
1 Online Early-Late Fusion Based on Adaptive HMM for Sign Language Recognition
1.1 Introduction
1.2 Adaptive HMMs
1.3 Early-Late Fusion
1.3.1 Feature Selection
1.3.2 Query-Adaptive Weighting
1.3.3 Score Fusion
1.4 Experiments
1.4.1 Experiments Setup
1.4.2 Experiment with HMM-States Adaptation
1.4.3 Comparison on Different Fusion Steps
1.4.4 Comparison on Different Dataset Sizes
1.4.5 Comparison on Different SLR Models
2 Hierarchical LSTM for Sign Language Translation
2.1 Introduction
2.2 Online Key Clip Mining
2.3 Hierarchical LSTM Encoder
2.3.1 Hierarchical Encoder
2.3.2 Pooling Strategy
2.3.3 Attention-Based Weighting
2.4 Sentence Generation
2.5 Experiment
2.5.1 Experiment Setup
2.5.2 Model Validation
2.5.3 Comparison to Existing Methods
3 Dense Temporal Convolution Network for Sign Language Translation
3.1 Introduction
3.2 DenseTCN
3.3 Sentence Learning
3.3.1 CTC Decoder
3.3.2 Score Fusion and Translation
3.4 Experiments
3.4.1 Datasets
3.4.2 Evaluation Metrics
3.4.3 Implementation Details
3.4.4 Depth Discussion
3.4.5 Comparison
4 Joint Optimization for Translation and Sign Labeling
4.1 Introduction
4.2 Clip Feature Learning in Videos
4.3 Joint Loss Optimization
4.3.1 CTC Loss for CTTR Module
4.3.2 Cross-Entropy Loss for FCLS Module
4.3.3 Triplet Loss for FCOR Module
4.4 Experiment
4.4.1 Experiment Setup
4.4.2 Model Validation
4.4.3 Main Comparison
References
Fusion-Based Image Enhancement and Its Applicationsin Mobile Devices
1 Introduction
2 Related Works
3 Fusion-Based Enhancement Models
3.1 A General Framework of Linear Fusion
3.2 Naturalness-Preserving Low-Light Enhancement
3.3 Mixed Pencil Drawing Generation
4 Applications in Mobile Devices
4.1 FFT Acceleration
4.2 Interactive Segmentation
4.3 Experimental Results
5 Conclusion and Discussion
References
Open-Domain Textual Question Answering Systems
1 Introduction
2 Overview of Open-Domain Question Answering Systems
3 Paragraph Ranking
3.1 Multi-Level Fused Sequence Matching Model
3.1.1 Multi-Level Fused Encoding
Foreword
Preface
Contents
About the Editors
Part I Vision-Based Technologies for Accessible Human Computer Interfaces
A Framework for Gaze-Contingent Interfaces
1 Introduction
1.1 Gaze-Contingent Interface
1.2 Eye Tracking and Gaze Detection
1.3 Gaze-Contingent Interface Based on Near Infrared Camera of Mobile Device
2 Methods
2.1 Framework
2.2 Calibration and Standard Acquisition
2.3 Determination of Sagittal Plane
2.4 Calculation of POG with Head Adjustment
2.5 Gaze Prediction by LSTM
2.6 Measurement of Head and Eye Movements
3 Use Cases
3.1 Use Case #1: Select an Option on Screen
3.2 Use Case #2: Auto Screen Scrolling
4 Future Work
References
Sign Language Recognition
1 Online Early-Late Fusion Based on Adaptive HMM for Sign Language Recognition
1.1 Introduction
1.2 Adaptive HMMs
1.3 Early-Late Fusion
1.3.1 Feature Selection
1.3.2 Query-Adaptive Weighting
1.3.3 Score Fusion
1.4 Experiments
1.4.1 Experiments Setup
1.4.2 Experiment with HMM-States Adaptation
1.4.3 Comparison on Different Fusion Steps
1.4.4 Comparison on Different Dataset Sizes
1.4.5 Comparison on Different SLR Models
2 Hierarchical LSTM for Sign Language Translation
2.1 Introduction
2.2 Online Key Clip Mining
2.3 Hierarchical LSTM Encoder
2.3.1 Hierarchical Encoder
2.3.2 Pooling Strategy
2.3.3 Attention-Based Weighting
2.4 Sentence Generation
2.5 Experiment
2.5.1 Experiment Setup
2.5.2 Model Validation
2.5.3 Comparison to Existing Methods
3 Dense Temporal Convolution Network for Sign Language Translation
3.1 Introduction
3.2 DenseTCN
3.3 Sentence Learning
3.3.1 CTC Decoder
3.3.2 Score Fusion and Translation
3.4 Experiments
3.4.1 Datasets
3.4.2 Evaluation Metrics
3.4.3 Implementation Details
3.4.4 Depth Discussion
3.4.5 Comparison
4 Joint Optimization for Translation and Sign Labeling
4.1 Introduction
4.2 Clip Feature Learning in Videos
4.3 Joint Loss Optimization
4.3.1 CTC Loss for CTTR Module
4.3.2 Cross-Entropy Loss for FCLS Module
4.3.3 Triplet Loss for FCOR Module
4.4 Experiment
4.4.1 Experiment Setup
4.4.2 Model Validation
4.4.3 Main Comparison
References
Fusion-Based Image Enhancement and Its Applicationsin Mobile Devices
1 Introduction
2 Related Works
3 Fusion-Based Enhancement Models
3.1 A General Framework of Linear Fusion
3.2 Naturalness-Preserving Low-Light Enhancement
3.3 Mixed Pencil Drawing Generation
4 Applications in Mobile Devices
4.1 FFT Acceleration
4.2 Interactive Segmentation
4.3 Experimental Results
5 Conclusion and Discussion
References
Open-Domain Textual Question Answering Systems
1 Introduction
2 Overview of Open-Domain Question Answering Systems
3 Paragraph Ranking
3.1 Multi-Level Fused Sequence Matching Model
3.1.1 Multi-Level Fused Encoding