Environmental Audio Information Perception

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Table of contents

CHAPTER 1. GENERAL INTRODUCTION
1.1. FOREWORD
1.2. BIOLOGICAL BACKGROUND
1.2.1. Human Perception System
1.2.2. Selective Attention Mechanism
1.3. MOTIVATION AND OBJECTIVES
1.4. CONTRIBUTION
1.5. ORGANIZATION OF THESIS
CHAPTER 2. SALIENT ENVIRONMENTAL INFORMATION PERCEPTION – STATE OF THE ART
2.1. INTRODUCTION
2.2. AUTONOMOUS OBJECT PERCEPTION USING VISUAL SALIENCY
2.2.1. Introduction
2.2.2. Object Detection using Visual Saliency
2.2.2.1. Basic Visual Saliency Model
2.2.2.2. State of the Art Methods
2.2.3. Autonomous Object Recognition and Classification
2.2.3.1. Image Feature Acquisition
2.2.3.1.1. Local point feature
2.2.3.1.2. Statistical Feature
2.2.3.2. Current Recognition Models
2.3. SALIENT ENVIRONMENT SOUND PERCEPTION
2.3.1. General Introduction
2.3.2. Auditory Saliency Detection
2.3.2.1. Motivation
2.3.2.2. Saliency Detection Models
2.3.3. Environmental Audio Information Perception
2.3.3.1. Feature Extraction of Audio Signal
2.3.3.2. Environmental Sound Recognition
2.4. AUDIO-VISUAL FUSION FOR HETEROGENEOUS INFORMATION OF SOUND AND IMAGE
2.5. CONCLUSION
CHAPTER 3. THE DETECTION AND CLASSIFICATION OF ENVIRONMENTAL SOUND BASED ON AUDITORY SALIENCY FOR ARTIFICIAL AWARENESS
3.1. INTRODUCTION
3.2. OVERVIEW OF THE APPROACH
3.3. HETEROGENEOUS SALIENCY FEATURES CALCULATION
3.3.1. Background Noise Estimation
3.3.1.1. Shannon Entropy
3.3.1.2. Short-term Shannon Entropy
3.3.2. Temporal Saliency Feature Extraction
3.3.2.1. MFCC based Saliency Calculation
3.3.2.2. Computational IOR Model for Feature Verification
3.3.3. Spectral Saliency Feature Extraction
3.3.3.1. Power Spectral Density
3.3.3.2. PSD based Saliency Calculation
3.3.4. Image Saliency Detection from Spectrogram
3.3.4.1. Log-Scale Spectrogram
3.3.4.2. Image Saliency Calculation based on Opponent Color Space
3.3.5. Heterogeneous Saliency Feature Fusion
3.4. MULTI-SCALE FEATURE BASED SALIENT ENVIRONMENTAL SOUND RECOGNITION
3.4.1. General Introduction
3.4.2. Multi-Scale Feature Selection
3.4.2.1. Fuzzy Set Theory
3.4.2.2. Fuzzy Vector based Feature Extraction
3.4.2.3. Acoustic Features Calculation
3.4.3. Classification Approach
3.5. EXPERIMENTS
3.5.1. Validation of Salient Environmental Sound Detection
3.5.1.1. Data Setup
3.5.1.2. Experimental Protocol
3.5.1.3. Verification Results and Discussion
3.5.2. Experiments of Real Environmental Sound Recognition
3.5.2.1. Experiment Setup
3.5.2.2. Experimental Protocol
3.5.2.3. Recognition Results
3.5.2.4. Discussion
3.6. CONCLUSION
CHAPTER 4. SALIENT INFORMATION BASED AUTONOMOUS ENVIRONMENTAL OBJECT DETECTION AND CLASSIFICATION
4.1. INTRODUCTION
4.2. OVERVIEW OF THE APPROACH
4.3. SPARSE REPRESENTATION BASED SALIENT ENVIRONMENTAL OBJECT DETECTION
4.3.1. Image Feature Extraction
4.3.1.1. Gabor Filter
4.3.1.2. 2-D Gabor Feature Extraction
4.3.2. Visual Saliency Detection
4.3.3. Sparse Representation based Foreground Objectness Detection
4.3.3.1. Motivation
4.3.3.2. Background Dictionary Learning
4.3.3.3. Foreground Object Detection based on Representation Error
4.3.4. Fusion Discrimination
4.4. SALIENT FOREGROUND ENVIRONMENTAL OBJECT CLASSIFICATION
4.4.1. General Introduction
4.4.2. Object Feature Extraction
4.4.3. Model Training
4.5. SIMULATION EXPERIMENTS
4.5.1. Experiment Setup
4.5.1.1. Data Setup
4.5.1.2. Experimental Protocol
4.5.2. Experiments Result and Discussion
4.6. CONCLUSION
CHAPTER 5. HETEROGENEOUS INFORMATION FUSION FRAMEWORK FOR HUMAN-LIKE PERCEPTION OF COMPLEX ENVIRONMENT
5.1. INTRODUCTION
5.2. PROPOSAL OF FRAMEWORK
5.3. PROBABILITY TOPIC MODEL BASED HETEROGENEOUS INFORMATION REPRESENTATION
5.3.1. Probability Topic Model
5.3.2. Information Probability Model
5.3.3. Heterogeneous Information Modeling
5.3.4. Scene Information Probability Model
5.4. HETEROGENEOUS INFORMATION FUSION BASED ENVIRONMENT PERCEPTION
5.4.1. Motivation
5.4.2. Negative Property based Complex Scene Modeling
5.4.3. Heterogeneous Model Fusion based Perception
5.5. EXPERIMENTAL VALIDATION
5.5.1. Experiment Setup
5.5.2. Experiments Result and Discussion
5.6. CONCLUSION
GENERAL CONCLUSION
CONCLUSION
PERSPECTIVES
PUBLICATIONS
BIBLIOGRAPHY