Advances in Visual Computing 19th International Symposium, ISVC 2024, Lake Tahoe, NV, USA, October 21–23, 2024, Proceedings, Part II

This two-volume set LNCS 15046 and 15047 constitutes the refereed proceedings of the 17th International Symposium, ISVC 2024, held at Lake Tahoe, NV, USA, during October 21-23, 2024.
The 54 (60) full papers and 12 poster papers were carefully reviewed and selected from 120 submissions. A total of 8 (13) papers were also accepted for oral presentation in special tracks from 15 submissions. The papers cover the following topical sections:
Part I: Deep Learning; Computer Graphics; Video Analysis and Event Recognition; Motion and Tracking; Detection and Recognition; Visualization, and Medical Image Analysis.
Part II: Segmentation; Recognition; Generalization in Visual Machine Learning; Vision and Robotics for Agriculture; Virtual Reality; Applications, and Poster.

Segmentation: Generating Synthetic Tree Point Clouds for Deep Learning Applications in Remote Sensing.- Image Segmentation by Latent Space Phase-Gating with Applications in High-Content Screening.- Evaluating Segmentation of Human Body Parts across Datasets. Recognition: Unsupervised Effectiveness Estimation Measure Based on Rank Correlation for Image Retrieval.- VLPSR: Enhancing Zero-shot Object ReID with Vision-language Model.- Sign Language Recognition using Visual Hand Landmarks and the Parameters of American Sign Language. ST: Generalization in Visual Machine Learning: Self-Supervised Segmentation to Pose Estimation Model for Mechanical Systems with Complex Kinematics.- Selective Noise-Aided Machine Unlearning with Deep Feature Visualization.- Investigating the Impact of a Foundational Medical Image Model for CT Classification. ST: Vision and Robotics for Agriculture: Vision-based Xylem Wetness Classification in Stem Water Potential Determination.- HydroVision: LiDAR-Guided Hydrometric Prediction with Vision Transformers and Hybrid Graph Learning.- Machine Vision and Deep Learning, for Robotic Harvesting of Shiitake Mushrooms.- Video analyses of Water Drop Penetration Time Using Temporal Action Localization for Evaluating Soil Water Repellency.- SAMPLS: A prompt engineering approach using Segment-Anything-Model for PLant Science research. Virtual Reality: Impact of Relevant Augmented Reality Information on Human Performance.- Toward Dynamic NPC Interactions: Integrating GPT-Driven Agents in 3D Virtual Environments.- Exploring Ecological Validity: A Comparative Study of the Mere Exposure Effect on Screens and in Immersive Virtual Reality.- Increasing Training Effciency of Motion-Intensive Virtual Reality Training with Adaptations based on Physiological Measurement Data. Applications: Leveraging Zero-Shot Learning on Street-View Imagery for Built Environment Variable Analysis.- Enhancing Classification of Aquatic Species through Supervised Contrastive Learning and Advanced Image Super-Resolution.- Automated Corrosion Identification in Metal Imagery: Traditional vs. Deep Learning.- Underwater Image Restoration using Light Attenuation.- HCC: An explainable framework for classifying discomfort from video. Poster: Enhanced Maritime Safety through Deep Learning and Feature Selection.- Discrete Anomalous Regions (DAR) - going beyond heatmaps and predicting actionable discrete regions.- Learning Flight Path Based on Recording Image and Flight Operation.- MobileNetV2-Enhanced Depth Map Super-Resolution through Multi-Scale Image Guidance.- Road Surface Material Recognition from Dashboard Cameras.- Embedded-ViT: A Framework for Embedded Deployment of Vision-Transformer in Medical Applications.- An Image-Based Method for Defect Detection on Metal Surfaces.- Real-Time Evaluation of Aircraft Instruments.- Enhancing Learned Image Compression via Cross Window-based Attention.- A Design of Real-Time Style-Transfer Operations in a Game Engine.- PLOV: A Visualization Tool For Exploring Visibility in Family Living Situations.- Exploring Gesture-Based Interaction in Smartwatch Games: A Comparative Study between Continuous Gesture Recognition and Hidden Markov Models.