2nd EAI International Conference on Robotic Sensor Networks (eBook)

ROSENET 2018

Huimin Lu, Li Yujie (Herausgeber)

eBook Download: PDF
2019 | 1st ed. 2020
X, 222 Seiten
Springer International Publishing (Verlag)
978-3-030-17763-8 (ISBN)

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This book provides scientific research into Cognitive Internet of Things for Smart Society, with papers presented at the 2nd EAI International Conference on Robotic Sensor Networks. The conference explores the integration of networks and robotic technologies, which has become a topic of increasing interest for both researchers and developers from academic fields and industries worldwide. The authors posit that big networks will be the main approach to the next generation of robotic research, with the explosive number of networks models and increasing computational power of computers significantly extending the number of potential applications for robotic technologies while also bringing new challenges to the network's community. The 2nd EAI International Conference on Robotic Sensor Networks was held 25-26 August 2018 at the Kitakyushu International Conference Center (MICE), Kitakyushu, Japan. 



Huimin Lu received a B.S. degree in Electronics Information Science and Technology from Yangzhou University in 2008. He received M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2011. He received a Ph.D. degree in Electrical Engineering from Kyushu Institute of Technology in 2014. From 2013 to 2016, he was a JSPS research fellow (DC2, PD, and FPD) at Kyushu Institute of Technology. Currently, he is an Assistant Professor in Kyushu Institute of Technology and an Excellent Young Researcher of MEXT-Japan. His research interests include computer vision, robotics, artificial intelligence, and ocean observing.

 

Yujie Li received the B.S. degree in Computer Science and Technology from Yangzhou University in 2009. She received M.S. degrees in Electrical Engineering from Kyushu Institute of Technology and Yangzhou University in 2012, respectively. She received a Ph.D. degree from Kyushu Institute of Technology in 2015. From 2016 to 2017, she was a Lecturer in Yangzhou University. Currently, she is an Assistant Professor in Fukuoka University, Japan and JSPS Research Fellow in Kyushu Institute of Technology, Japan. Her research interests include computer vision, sensors, and image segmentation.

Preface 6
Conference Organization 7
Contents 9
New Tuning Formulas: Genetic Algorithm Used in Air Conditioning Process with PID Controller 11
1 Introduction 11
2 PID Controller Structure Design and Parameters Tuning 12
2.1 Two Degrees-of-Freedom PID Control Structure 12
2.2 Solution of Optimization Problem Using Genetic Algorithm 13
3 Derivation of the New Tuning Formulas 15
3.1 Test Batch 15
3.2 Apply Optimization Procedures 15
3.3 New Tuning Formulas 15
4 Results 16
5 Conclusion 18
References 18
A Multi-Level Thresholding Image Segmentation Based on an Improved Artificial Bee Colony Algorithm 20
1 Introduction 20
2 ABC Algorithm 21
3 Otsu Segmentation Algorithm 22
4 An Improved ABC Algorithm 23
4.1 Analysis on the Otsu 23
4.2 An Improved ABC 24
5 Experiment 25
5.1 Experimental Setting 25
5.2 Experimental Results 25
6 Conclusion 27
References 27
Dynamic Consolidation Based on Kth-Order Markov Model for Virtual Machines 29
1 Introduction 29
2 Related Work 30
3 System Design 32
3.1 System Model 32
3.2 Algorithm 34
4 Experiment 34
4.1 Experimental Design 34
4.2 Analysis 35
5 Conclusions 37
References 37
Research into the Adaptability Evaluation of the Remote Sensing Image Fusion Method Based on Nearest-Neighbor Diffusion Pan Sharpening 40
1 Introduction 40
2 Fusion Effect Evaluation 41
2.1 Evaluating the Image Information Index 41
2.2 Index of Evaluating the Ability of Image Spatial Information Retention 42
2.3 Index of Evaluating Image Spectral Information Retention 42
3 Experiment and Analysis 43
3.1 Experimental Data 43
3.2 Experimental Results and Discussion 43
4 Conclusion 45
References 45
Estimation of Impervious Surface Distribution by Linear Spectral Mixture Analysis: A Case Study in Nantong, China 47
1 Introduction 47
2 Data and Method 48
2.1 Overview of Study Area and Data Source 48
2.2 Inversion of Impervious Surface Information 49
2.2.1 Minimum Noise Fraction (MNF) 49
2.2.2 Extraction of Pixel 49
3 Results and Discussion 51
3.1 Abundant Images of Four Pixels 51
3.2 Impervious Surface Percentage (ISP) Distribution Diagram 51
3.3 Precision Verification 53
4 Conclusions 56
References 56
Marine Organisms Tracking and Recognizing Using YOLO 58
1 Introduction 58
2 Dataset 58
3 System Configuration 59
3.1 Haze Removal on Deep-Sea Images 59
3.2 Detecting and Tracking Marine Organisms 60
4 Experimental Results and Discussions 61
5 Conclusion 63
References 63
Group Recommendation Robotics Based on External Social-Trust Networks 64
1 Introduction 64
2 Related Work 65
2.1 Group Recommendation Robotics 65
2.2 Social Network Recommendation Robotic 66
3 External-Based Social-Trust Networks Group Recommendation Robotics 67
3.1 GRR Calculation Framework 67
3.2 Dynamic Adjustment of Parameter ? 69
3.3 Group Recommendation Robotics Based on External Social-Trust Networks 70
4 Experiments 72
4.1 Experimental Data 72
4.2 Evaluation Method Description 72
4.3 Randomly Divided into Groups Experiment 73
4.4 Social-Trust Network Utilization Ratio in Group Recommendations 74
5 Conclusion 75
References 76
Vehicle Logo Detection Based on Modified YOLOv2 79
1 Introduction 79
1.1 Research Significance 79
1.2 Technical Difficulties 79
1.3 Typical Vehicle Logo Detection Algorithm 80
2 Construction of Datasets 81
2.1 Data Acquisition 81
2.2 Data Enrichment 82
2.2.1 Brightness Transforms 83
2.2.2 Gaussian Noise 83
3 Analysis and Improvement 84
3.1 YOLOv2 Algorithm 84
3.1.1 Darknet19 84
3.1.2 Competitive Advantage 84
3.2 Improvement Based on YOLOv2 85
3.2.1 K-Means Clustering 85
3.2.2 Network Pre-Training 86
3.2.3 Multi-Scale Detection Training 87
4 Experimental Design and Interpretation of Results 87
4.1 Comparative Experiment 87
4.2 Experimental Results and Analysis 87
4.2.1 Comparison Experiment on the Four Algorithms 87
4.2.2 Comparison Experiment on the Improved Algorithm 88
References 90
Energy-Efficient Virtual Machines Dynamic Integration for Robotics 91
1 Introduction 91
2 Related Works 93
3 K-Order Mixed Markov Model 95
4 Host Model 97
4.1 Model Establishment 97
4.2 Algorithm Design 100
5 Experiment and Result Analysis 102
5.1 The Experimental Process 102
5.2 Analysis of Simulation Results 104
6 Conclusion 108
References 108
Multi-Level Chaotic Maps for 3D Textured Model Encryption 111
1 Introduction 111
2 Previous Work 112
3 Preliminaries 113
3.1 1D Logistic Map 113
3.2 2D Arnold's Cat Map 113
3.3 3D Lu Map 114
4 Multi-Level 3D Model Encryption 114
4.1 Vertices Encryption 114
4.2 Polygons Encryption 115
4.3 Textures Encryption 116
5 Simulation Performance 116
6 Security and Performance Analysis 117
6.1 Resistance to the Brute-Force Attack 117
6.2 Resistance to the Statistic Attack 118
6.3 The Speed of the Encryption and Decryption 119
7 Conclusions 120
References 120
Blind Face Retrieval for Mobile Users 122
1 Introduction 122
2 Problem Formulation 124
2.1 Overview 124
2.2 Security Model 124
3 Secure Face Retrieval 126
3.1 Secure Face Detection 126
3.2 Face Recognition and Label Vector 127
3.3 Secure Face Label Matching 127
4 Experiments 128
5 Conclusion 129
References 129
Near-Duplicate Video Cleansing Method Based on Locality Sensitive Hashing and the Sorted Neighborhood Method 131
1 Introduction 131
2 Related Work 132
3 Near-Duplicate Video Cleansing Method Based on LSH and SNM 133
3.1 Key Frame Extraction of Video Data 133
3.2 Feature Extraction of Local Key-Points 134
3.3 Near-Duplicate Video Cleansing Method Based on LSH and SNM 136
4 Experimentation and Analysis 137
5 Conclusion 140
References 141
A Double Auction VM Migration Approach 142
1 Introduction 142
2 Related Work 143
3 System Model 143
4 VM Migration Algorithm 144
4.1 VMs-GSA Design 144
4.2 VMM-DAM Design 145
5 Results and Conclusion 146
References 147
An Auction-Based Task Allocation Algorithm in Heterogeneous Multi-Robot System 149
1 Introduction 149
2 Related Work 150
3 Model Description and Notations 151
3.1 Definitions of Notations and Model 151
4 Static Auction Algorithm Description 152
5 Experimental Results and Future Work 154
References 155
Non-uniformity Detection Method Based on Space-TimeAutoregressive 157
1 Introduction 157
2 The Basic Principle of Star Algorithm 158
3 Cascade Star Algorithm 160
3.1 Anti-Interference Target STAR Algorithm 160
3.2 Cascade STAR Algorithm 162
4 Simulation Results and Analysis 164
5 Conclusions 167
References 167
Secondary Filter Keyframes Extraction Algorithm Based on Adaptive Top-K 169
1 Introduction 169
2 Related Work 170
3 Secondary Filter Key Frame Extraction Algorithm 171
3.1 Video Sequence Moving Target Detection 171
3.2 Image Eigenvalue Calculation of Video Frames 172
3.3 Adaptive Threshold Calculation 173
3.4 Secondary Filter Keyframe Extraction 174
4 Experimentation and Analysis 176
5 Conclusion 176
References 179
An Introduction to Formation Control of UAV with Vicon System 181
1 Introduction 181
2 System Framework 182
2.1 Hardware Setup 182
2.2 Software Architecture 184
3 Experimental Setup 186
3.1 Control Algorithm 186
3.2 Results and Analysis 186
4 Conclusion and Future Work 188
References 189
Quadratic Discriminant Analysis Metric Learning Based on Feature Augmentation for Person Re-Identification 191
1 Introduction 191
2 Related Work 192
3 Approach 192
3.1 A Brief Introduction to XQDA 192
3.2 Feature Augmentation 194
3.3 The Proposed Approach 194
4 Experiment 196
5 Conclusion 197
References 198
Weighted Linear Multiple Kernel Learning for Saliency Detection 200
1 Introduction 200
2 The Proposed Method 202
2.1 Image Representation 202
2.2 Computing Contrast Feature Maps 203
2.3 WLMKL Framework 204
3 Experiments 208
3.1 Experimental Setting 208
3.2 Results and Analysis 208
4 Conclusion 210
References 210
Index 213

Erscheint lt. Verlag 1.7.2019
Reihe/Serie EAI/Springer Innovations in Communication and Computing
EAI/Springer Innovations in Communication and Computing
Zusatzinfo X, 222 p. 71 illus., 61 illus. in color.
Sprache englisch
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Technik Elektrotechnik / Energietechnik
Technik Maschinenbau
Schlagworte Artificial Intelligence and Robotic Sensor Networks • Communications and Robotic Sensor Networks • Computer Vision and Robotic Sensor Networks • Electronics and Robotic Sensor Networks • Internet of Things and Robotic Sensor Networks • Multimedia and Robotic Sensor Networks
ISBN-10 3-030-17763-7 / 3030177637
ISBN-13 978-3-030-17763-8 / 9783030177638
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