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ویرایش: نویسندگان: Yongtian Wang, Xueming Li, Yuxin Peng سری: Communications in Computer and Information Science, 1314 ISBN (شابک) : 9813360321, 9789813360327 ناشر: Springer Singapore سال نشر: 2021 تعداد صفحات: 327 زبان: English فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 72 Mb
در صورت تبدیل فایل کتاب Image and Graphics Technologies and Applications: 15th Chinese Conference, IGTA 2020, Beijing, China, September 19, 2020, Revised Selected Papers به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب فن آوری ها و برنامه های تصویر و گرافیک: پانزدهمین کنفرانس چینی ، IGTA 2020 ، پکن ، چین ، 19 سپتامبر 2020 ، مقاله های منتخب اصلاح شده نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
Preface Organization Contents Image Processing and Enhancement Techniques Single Image Super-Resolution Based on Generative Adversarial Networks Abstract 1 Introduction 2 Related Work 3 Proposed Method 3.1 Network Structure 3.2 Densely Connected Dilated Convolution 3.3 Channel Attention Mechanism 4 Experiment 4.1 Experiment Preparation 4.2 Experiment Results 4.3 Ablation Experiment 5 Conclusion References A Striping Removal Method Based on Spectral Correlation in MODIS Data Abstract 1 Introduction 2 The Proposed Destriping Algorithm 2.1 Auto Piecewise Moment Matching Method Based on Genetic Algorithm(GA) 2.2 Fourier Low-Pass Filtering of Residual Noise of High Correlation Band 3 Experiment Results 4 Conclusions References Multi-modal 3-D Medical Image Fusion Based on Tensor Robust Principal Component Analysis Abstract 1 Introduction 2 Related Works 3 Proposed Method 3.1 Procedures of Proposed Method 3.2 3-D Weighted Local Laplacian Energy Rule 4 Experiments 4.1 Experimental Setting 4.2 Comparison on the Synthetic Data 4.3 Comparison on the Real Data 5 Conclusion Acknowledgements References Accurate Estimation of Motion Blur Kernel Based on Genetic Algorithms Abstract 1 Introduction 2 Related Works 2.1 Traditional Methods 2.2 Machine Learning Methods 3 Motion Blur Kernel Estimation Based on Genetic Algorithms 3.1 Individual Representation 3.2 Initialization of the First Generation Population 3.3 Genetic Operators 3.4 Fitness Function 3.5 Parameter Setting 4 Experiment and Analysis 4.1 Sample Data of Blur Kernel Estimation 4.2 The Rough Estimation Process of Motion Blur Kernel 4.3 Blur Kernel Estimation Results 5 Conclusion Acknowledgment References Biometric Identification Techniques Graph Embedding Discriminant Analysis and Semi-Supervised Extension for Face Recognition Abstract 1 Introduction 2 Related Works 2.1 Marginal Fisher Analysis (MFA) 2.2 Graph Discriminant Embedding (GDE) 3 Methodology 3.1 The Proposed Method 3.2 Semi-Supervised Extension (SSE) 3.3 Algorithm 4 Experiments 4.1 Experiments on ORL Dataset 4.2 Experiments on AR Dataset 4.3 Experiments on FERET Dataset 4.4 Experiments Under Noise Condition 4.5 Experiments Under Blur Condition 5 Conclusion Acknowledgments References Fast and Accurate Face Alignment Algorithm Based on Deep Knowledge Distillation Abstract 1 Introduction 2 Related Work 3 Methodology 3.1 Deep Knowledge Distillation Method 3.2 Model Structure of Deep Knowledge Distillation 3.3 Teacher Model and Student Model Analysis 3.4 Reasoning Complexity 4 Experimental Results and Analysis 4.1 Experimental Preparation 4.2 Evaluation Metrics 4.3 Experimental Details 4.4 Evaluation Results on 300W 4.5 Evaluation Results on WFLW 5 Conclusion References Machine Vision and 3D Reconstruction 3D Human Body Reconstruction from a Single Image Abstract 1 Introduction 2 Technical Methods 2.1 Overall Network Structure 2.2 Generative Network 2.3 Adversarial Network 2.4 3D Joint Angle Limitation 2.5 Loss of the Network Model 3 Experimental Results 4 Conclusion Funding. References Image/Video Big Data Analysis and Understanding Abnormal Crowd Behavior Detection Based on Movement Trajectory Abstract 1 Introduction 2 Multiple Object Tracking Based on Detection 3 Abnormal Behaviour Detection of the Crowd 3.1 Abnormal Direction 3.2 Abnormal Crossing 3.3 Trajectory Traceback 4 Experiments and Analysis Results 4.1 Experimental Setup 4.2 Experimental Analysis 5 Conclusion Acknowledgment References Full Convolutional Color Constancy with Attention Abstract 1 Introduction 2 Related Work 3 Attention Structure Design 3.1 Channel Attention Mechanism 3.2 Spatial Attention Mechanism 3.3 Mixed Attention Mechanism 3.4 Network Structure 4 Experiments 5 Conclusion References Simplifying Sketches with Conditional GAN Abstract 1 Introduction 2 Related Work 2.1 Sketch Simplification 2.2 Conditional GAN 3 Architecture 3.1 Overview 3.2 CGAN 3.3 Loss Function 4 Experiment 4.1 Platform 4.2 Dataset 4.3 Training Details 5 Evaluation 5.1 Comparison with the State of the Art 5.2 User Study 6 Conclusion References Improved Method of Target Tracking Based on SiamRPN Abstract 1 Introduction 2 Baseline 2.1 SiamRPN 2.2 Region Proposal Network 3 Proposed Method 3.1 Convolutional Block Attention Module 3.2 Squeeze-and-Excitation Module 4 Experiment and Analysis 4.1 Datasets and Evaluation Criteria 4.2 Implementation Details 4.3 Experiment 1: Comparison of CAM Visualization Results of the Feature Extraction Networks 4.4 Experiment 2: Comparison with the Baseline Method SiamRPN on OTB2015 4.5 Experiment 3: Comparison with Other Tracking Methods on OTB2015 4.6 Experiment 4: Comparison with Other Tracking Methods on VOT2016 5 Conclusion Acknowledgments References An Improved Target Tracking Method Based on DIMP Abstract 1 Introduction 2 Baseline 2.1 Discriminative Learning Loss 2.2 Model Predictor 3 Proposed Method 3.1 Information Flow Through the Network 3.2 Projected Shortcut 4 Experiment and Analysis 4.1 Experiment 1: Selection of Model Training Rounds for Epoch 4.2 Experiment 2: Comparison Between Our Method and DIMP 4.3 Experiment 3: Robustness Analysis of Our Methodology and Some Mainstream Tracking Methods 4.4 Experiment 4: The Applicability of Our Method for Other Algorithms 5 Conclusion Acknowledgments References Infrared Small Target Recognition with Improved Particle Filtering Based on Feature Fusion Abstract 1 Introduction 2 Algorithm Framework 2.1 Preprocessing 2.2 Gray Feature Extraction 2.3 Motion Feature Extraction 2.4 Improved Particle Filter Algorithm Optimized by Krill Herd 3 Simulation Results and Analysis 4 Conclusions References Target Recognition Framework and Learning Mode Based on Parallel Images Abstract 1 Introduction 2 Establishment of Artificial Image Data Set 2.1 Artificial Image Generation Method 2.2 Data Set Structure 3 Target Recognition Framework Based on Parallel Images 4 Insulator Recognition Experiment Based on PITR Framework 4.1 Experiment 4.2 Structure of Sample Classification Network 4.3 Results and Discussion 5 Conclusion References Crowd Anomaly Scattering Detection Based on Information Entropy Abstract 1 Introduction 2 Multi-target Detection and Tracking 3 Scattered Detection Method of Crowd Abnormality 3.1 Movement Speed Factor of the Crowd 3.2 The Information Entropy of the Crowd 3.3 Evaluation Method 4 Experiments and Analysis Results 4.1 Experiments Setup 4.2 Experimental Analysis Based on Three Scenarios 5 Conclusion Acknowledgments References Computer Graphics View Consistent 3D Face Reconstruction Using Siamese Encoder-Decoders 1 Introduction 2 Related Work 2.1 3D Morphable Model 2.2 Learning-Based Methods 2.3 High-Fidelity Face Reconstruction 3 The Proposed Method 3.1 Siamese Network for Consistent Texture and Normal Map 3.2 Network Architecture 3.3 Loss Functions 4 Experiments 4.1 Implementation Details 4.2 Analysis on the Siamese Network 4.3 Analysis on the Normal Refinement 4.4 Comparison with the State-of-the-art Methods 5 Conclusion References An Angle-Based Smoothing Method for Triangular and Tetrahedral Meshes Abstract 1 Introduction 1.1 Laplacian Smoothing 1.2 Variations of Laplacian Smoothing 1.3 Optimization-Based Smoothing 1.4 Combinations of Laplacian Smoothing and Optimization-Based Smoothing 1.5 Our Contributions 2 Related Work 2.1 Laplacian Smoothing 2.2 Smart Laplacian Smoothing 3 Another Way to Understand Laplacian Smoothing 4 Angle-Based Smoothing Method 4.1 Angle-Based Smoothing for Triangular Meshes 4.2 Angle-Based Smoothing for Tetrahedral Meshes 5 Examples and Analysis 5.1 Examples 5.2 Analysis 6 Conclusions and Future Work References Virtual Reality and Human-Computer Interaction Rendering Method for Light-Field Near-Eye Displays Based on Micro-structures with Arbitrary Distribution Abstract 1 Introduction 2 Method 2.1 Light Field Rendering 2.2 Light Field Rendering System Based on Cameras with Arbitrary Distribution 3 Experiments and Results 3.1 The Light-Field Near-Eye Displays Simulation Experiment 3.2 Near-Eye Displays Using Random Holes and a Pinhole Array 4 Conclusion Acknowledgments References AUIF: An Adaptive User Interface Framework for Multiple Devices 1 Introduction 2 Related Work 3 Design of AUIF 3.1 Multi-device Collaboration Patterns 3.2 UI Components Allocation Algorithm 3.3 DUI Generation Framework 4 Prototype System 5 User Study 5.1 Design of the Experiment 5.2 Result 6 Conclusions References Applications of Image and Graphics Control and on-Board Calibration Method for in-Situ Detection Using the Visible and Near-Infrared Imaging Spectrometer on the Yutu-2 Rover Abstract 1 Introduction 2 Control Method and Engineering Applications 2.1 Control Method 2.2 Engineering Applications 3 Error Analysis and on-Board Calibration 3.1 Error Analysis 3.2 On-Board Calibration 4 Conclusion Acknowledgments References Deep Attention Network for Remote Sensing Scene Classification Abstract 1 Introduction 2 The Proposed Method 2.1 Overview 2.2 Channel Attention 2.3 Spatial Attention 2.4 Branch Fusion 3 Experimental Results 4 Conclusion References Thin Cloud Removal Using Cirrus Spectral Property for Remote Sensing Images Abstract 1 Introduction 2 Methodology 2.1 Cirrus Spectral Property 2.2 Removal of Thin Cloud Effect 3 Experimental Results and Analysis 4 Conclusion References A Multi-line Image Difference Technique to Background Suppression Based on Geometric Jitter Correction Abstract 1 Introduction 2 A Multi-line Image Difference Technique to Background Suppression Based on Geometric Jitter Correction 2.1 Geometric Jitter Correction Based on Adaptive Correlation 2.1.1 Geometric Correction Preprocessing 2.1.2 Geometric Jitter Correction 2.2 A Multi-line Image Difference Technique to Background Suppression Based on Geometric Jitter Correction 3 Simulation and Experiment 3.1 Experiment on the Effectiveness of Geometric Registration Strategy 3.2 Image Jitter Correction Effect Verification Experiment 3.3 Resampling Algorithm Simulation 3.4 Differential Detection Effect Verification Experiment 4 Conclusion References Other Research Works and Surveys Related to the Applications of Image and Graphics Technology Image Recognition Method of Defective Button Battery Base on Improved MobileNetV1 Abstract 1 Introduction 2 Improved MobileNetV1 2.1 Basic Network 2.2 Double-Layer Asymmetric Convolution 2.3 Activation Function Replacement 3 Experiment Procedure 3.1 Button Battery Data Set 3.1.1 Data Collection and Data Procession 3.1.2 Tfrecord Data Format 3.2 Experimental Comparison and Analysis 3.2.1 Experimental Comparison of Different Activation Functions 3.2.2 Improve MobileNetV1 Performance 4 Conclusion References Author Index