LEADER 10835nam 22004813 450 001 9910746299903321 005 20230922080256.0 010 $a3-031-44137-0 035 $a(MiAaPQ)EBC30749667 035 $a(Au-PeEL)EBL30749667 035 $a(EXLCZ)9928272149600041 100 $a20230922d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputer Vision Systems $e14th International Conference, ICVS 2023, Vienna, Austria, September 27-29, 2023, Proceedings 205 $a1st ed. 210 1$aCham :$cSpringer,$d2023. 210 4$d©2023. 215 $a1 online resource (466 pages) 225 1 $aLecture Notes in Computer Science Series ;$vv.14253 311 08$aPrint version: Christensen, Henrik I. Computer Vision Systems Cham : Springer,c2023 9783031441363 327 $aIntro -- Preface -- Organization -- Contents -- Humans and Hands -- Tracking and Identification of Ice Hockey Players -- 1 Introduction -- 2 Related Work -- 2.1 Dataset -- 2.2 Player Detection -- 2.3 Player Tracking -- 2.4 Number Recognition -- 3 System Overview -- 3.1 Player Detection -- 3.2 Player Tracking -- 3.3 Player Identification -- 4 Results -- 4.1 Dataset -- 4.2 Player Tracking -- 4.3 Player Identification -- 5 Conclusion -- References -- Dedicated Encoding-Streams Based Spatio-Temporal Framework for Dynamic Person-Independent Facial Expression Recognition -- 1 Introduction -- 2 Related Works -- 3 Proposed Deep CNN-LSTM for Dynamic FER -- 4 Experimental Analysis -- 4.1 Dynamic FER Datasets -- 4.2 Evaluation of the Proposed CNN-LSTM -- 4.3 Comparison Against State-of-the-art -- 4.4 Confusion Matrix-Based Analysis -- 4.5 Ablation Study -- 4.6 Implementation Details and Running Time -- 5 Conclusion -- References -- Hands, Objects, Action! Egocentric 2D Hand-Based Action Recognition -- 1 Introduction -- 2 Related Work -- 3 Hand-Based 2D Action Recognition -- 3.1 Object Detection and Its Position -- 3.2 Hand Pose Estimation -- 3.3 Action Recognition -- 4 Evaluation -- 4.1 Learning Procedure -- 4.2 Stage I - Preliminary Evaluation -- 4.3 Stage II -Evaluation of a Complete Pipeline -- 4.4 Ablation Study -- 5 Conclusion -- References -- WiFi CSI-Based Long-Range Through-Wall Human Activity Recognition with the ESP32 -- 1 Introduction -- 2 Related Work -- 3 Experimental Setup -- 3.1 Hardware -- 3.2 Recording Environment -- 3.3 Data Collection and Pre-processing -- 4 Evaluation -- 4.1 Model Training -- 4.2 Presence Detection Results -- 4.3 Activity Recognition Results -- 5 Conclusion -- References -- PseudoDepth-SLR: Generating Depth Data for Sign Language Recognition -- 1 Introduction -- 2 Related Work -- 3 Methodology. 327 $a3.1 Proposed Architecture -- 3.2 Pseudo Depth Data Generation -- 4 Experimental Details -- 4.1 Dataset and Evaluation -- 4.2 Implementation Details -- 5 Results and Analysis -- 5.1 How Significant is Depth Data? -- 5.2 Comparison with State-of-the-Art Results -- 6 Ablation Study -- 6.1 Depth Flow Data -- 6.2 Pseudo Depth Data Generation -- 7 Conclusion -- References -- Slovo: Russian Sign Language Dataset -- 1 Introduction -- 2 Related Work -- 2.1 Sign Language Datasets in Russian Domain -- 2.2 Others Sign Language Datasets -- 2.3 Sign Language Dataset Collection -- 3 Dataset Creation -- 4 Dataset Description -- 5 Experiments -- 6 Conclusion -- References -- Non-contact Heart Rate Monitoring: A Comparative Study of Computer Vision and Radar Approaches -- 1 Introduction -- 2 Non-contact Heart Rate Monitoring -- 2.1 CV-Based HR Monitoring -- 2.2 Radar-Based HR Monitoring -- 3 CV and Radar-Based DMS Testbench Architectures -- 3.1 Proposed CV-Based HR Monitoring Architecture -- 3.2 Proposed Radar-Based HR Monitoring Architecture -- 4 Experiment Design and Results Analysis -- 4.1 Performance Validation -- 4.2 Variation of IBI Distribution with Sensor Modality -- 4.3 Impact of Distance on CV and Radar-Based HR Detection -- 4.4 Impact of Illumination on CV-Based HR Detection -- 4.5 Impact of Motion on CV and Radar-Based HR Detection -- 5 Discussion and Conclusions -- References -- Medical and Health Care -- CFAB: An Online Data Augmentation to Alleviate the Spuriousness of Classification on Medical Ultrasound Images -- 1 Introduction -- 2 Approach -- 2.1 Weakly Supervised Lesion Localization -- 2.2 Mixed Samples Generation -- 2.3 Collaborative Training Framework -- 3 Experiences -- 3.1 Implementation Details -- 3.2 Performance Comparison -- 3.3 Effectiveness of Lesion Localization -- 3.4 Ablation Studies -- 3.5 Visualization -- 4 Conclusion -- References. 327 $aTowards an Unsupervised GrowCut Algorithm for Mammography Segmentation -- 1 Introduction -- 2 Related Work -- 3 Proposed Method -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- DeepLabV3+ Ensemble for Diagnosis of Cardiac Transplant Rejection -- 1 Introduction -- 2 Related Work -- 3 Our Approach -- 3.1 Dataset -- 3.2 Data Preprocessing -- 3.3 DeepLabV3+ -- 3.4 Stacked U-Net -- 3.5 mU-Net++ -- 3.6 Post-processing -- 4 Results -- 4.1 Models Evaluation -- 5 Conclusions and Discussion -- References -- Farming and Forestry -- Of Mice and Pose: 2D Mouse Pose Estimation from Unlabelled Data and Synthetic Prior -- 1 Introduction -- 2 Related Work -- 3 Method -- 4 Experiments -- 5 Discussion and Conclusion -- References -- SIFT-Guided Saliency-Based Augmentation for Weed Detection in Grassland Images: Fusing Classic Computer Vision with Deep Learning -- 1 Introduction -- 2 Related Work -- 2.1 Rumex Detection -- 2.2 Augmentation in Deep Learning -- 3 Method -- 3.1 YOLOR -- 3.2 SIFT-Guided Saliency-Based Augmentation Module -- 4 Experimental Setup -- 4.1 Dataset -- 4.2 Metrics -- 4.3 Fixed Training Settings -- 5 Experiments -- 5.1 Baseline Performance -- 5.2 Ablation Study of Module Usage Probability psift -- 5.3 Ablation Study of Overlay Ratio rsift -- 6 Conclusion -- References -- Key Point-Based Orientation Estimation of Strawberries for Robotic Fruit Picking -- 1 Introduction -- 2 Related Work -- 3 The Approach -- 3.1 Key Point Detection -- 3.2 Key Point-Based Orientation -- 3.3 Improved Estimation of the Pitch Angle -- 4 Evaluation Setup -- 5 Results -- 6 Conclusions and Future Work -- References -- Residual Cascade CNN for Detection of Spatially Relevant Objects in Agriculture: The Grape-Stem Paradigm -- 1 Introduction -- 2 Related Work -- 2.1 Instance Segmentation -- 2.2 Object Detection in Agriculture -- 3 Motivation. 327 $a4 Method -- 4.1 Data Collection/Annotation -- 4.2 Yolo-V5 Architecture -- 4.3 Residual Connection of Detectors -- 5 Experimental Results -- 5.1 Evaluation -- 5.2 Conclusions -- References -- Improving Knot Prediction in Wood Logs with Longitudinal Feature Propagation -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Data Preprocessing -- 3.2 Neural Network Architectures Without Recurrent Connections -- 3.3 Neural Network Architectures with Recurrent Connections -- 3.4 Evaluation Metrics -- 3.5 Other Experimental Hyperparameters -- 4 Results -- 5 Discussion -- References -- Automation and Manufacturing -- Semi-Siamese Network for Robust Change Detection Across Different Domains with Applications to 3D Printing -- 1 Introduction -- 2 Related Work -- 3 Semi-Siamese Defect Detection Model -- 3.1 Transfer Learning from U-Net Models -- 3.2 Semi-Siamese Network Architecture -- 3.3 Training Objective -- 4 Experiments -- 4.1 Full Dataset Generation Using Data Augmentation -- 5 Results -- 6 Conclusions -- References -- Spatial Resolution Metric for Optimal Viewpoints Generation in Visual Inspection Planning -- 1 Introduction -- 2 Viewpoint Planning Problem Formulation -- 3 State of the Art of the VPP -- 4 Sampling Density Matrix -- 5 Results and Discussions -- 6 Conclusions and Outlook -- References -- A Deep Learning-Based Object Detection Framework for Automatic Asphalt Pavement Patch Detection Using Laser Profiling Images -- 1 Introduction -- 1.1 Visual Inspection -- 1.2 Related Work -- 2 Methodology -- 2.1 Data Collection & -- Preparation -- 2.2 Network Architecture -- 2.3 Evaluation Protocol -- 2.4 Experimental Results -- 2.5 Patch Detection on Different Pavement Conditions -- 3 Conclusion -- References -- A Flexible Approach to PCB Characterization for Recycling -- 1 Introduction -- 2 Approach -- 2.1 Dataset -- 3 Implementation. 327 $a3.1 Segmentation -- 3.2 Components Identification -- 3.3 Rule-Based Classification -- 3.4 ML Classifier -- 4 Results -- 4.1 Rule-Based vs ML Classifier -- 4.2 PCB Classification -- 5 Conclusion -- References -- SynthRetailProduct3D (SyRePro3D): A Pipeline for Synthesis of 3D Retail Product Models with Domain Specific Details Based on Package Class Templates -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Product Package Base Template Model -- 3.2 Object 3D Shape Augmentation -- 3.3 Generative Models for Domain-Specific Add-Ons -- 3.4 Base Texturing -- 3.5 Placing of Domain-Specific Add-Ons -- 4 Results -- 5 Conclusions -- References -- Small, but Important: Traffic Light Proposals for Detecting Small Traffic Lights and Beyond -- 1 Introduction -- 2 Related Work -- 3 Method -- 3.1 Traffic Light Proposal Generator -- 3.2 Traffic Light Detection Module -- 3.3 Training -- 4 Experiments -- 4.1 Quantitative Results -- 4.2 Qualitative Results -- 4.3 Ablation Studies -- 5 Conclusion -- References -- MATWI: A Multimodal Automatic Tool Wear Inspection Dataset and Baseline Algorithms -- 1 Introduction -- 2 Related Work -- 2.1 Datasets and Methods with Sensor Data -- 2.2 Datasets and Methods with Image Data -- 3 MATWI Dataset -- 3.1 Dataset Acquisition -- 3.2 Data Collection Conditions -- 3.3 Hardware Setup -- 3.4 Collected Data -- 4 Algorithms for Wear Estimation -- 4.1 Dataset Training/test Split -- 4.2 Regression Baseline -- 4.3 Histogram-Loss Based Embedding Learning -- 4.4 Quantitative Results -- 5 Conclusions -- 6 Future Work -- References -- Mixing Domains for Smartly Picking and Using Limited Datasets in Industrial Object Detection -- 1 Introduction -- 2 Related Work -- 3 Multi-domain Hybrid Datasets -- 3.1 Real Data Acquisition -- 3.2 Synthetic Data Generation -- 4 Experimentation and Results -- 4.1 Experimentation Setup. 327 $a4.2 Obtained Results and Discussion. 410 0$aLecture Notes in Computer Science Series 700 $aChristensen$b Henrik I$0845483 701 $aCorke$b Peter$027537 701 $aDetry$b Renaud$01429373 701 $aWeibel$b Jean-Baptiste$01429374 701 $aVincze$b Markus$01429375 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910746299903321 996 $aComputer Vision Systems$93568340 997 $aUNINA