2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)最新文献_第3页

CrowdAR Table - An AR Table for Interactive Crowd Simulation 一个用于交互式人群模拟的AR表

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00070

Wolfgang Hürst, Roland Geraerts, Yiran Zhao

引用次数: 2

A Case Study on Visual-Inertial Odometry using Supervised, Semi-Supervised and Unsupervised Learning Methods 基于监督、半监督和无监督学习方法的视觉惯性里程计实例研究

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00043

Yuan Tian, M. Compere

{"title":"A Case Study on Visual-Inertial Odometry using Supervised, Semi-Supervised and Unsupervised Learning Methods","authors":"Yuan Tian, M. Compere","doi":"10.1109/AIVR46125.2019.00043","DOIUrl":"https://doi.org/10.1109/AIVR46125.2019.00043","url":null,"abstract":"This paper presents a pilot study comparing three different learning-based visual-inertial odometry (VIO) approaches: supervised, semi-supervised, and unsupervised. Localization and navigation have been the ancient bur important topic in both research area and industry. Many well-developed algorithms have been established regarding this research task using a single sensor or multiple sensors. VIO, that uses images and inertial measurements to estimate the motion, is considered as one of the key technologies to virtual reality and argument reality. With the rapid development of artificial intelligence technology, people have started to explore new methods for VIO instead of traditional feature-based methods. The advantages of using learning-based method can be found in eliminating the calibration and enhance the robustness and accuracy. However, most of the popular learning-based VIO systems require ground truth during training. The lack of training dataset limits the power of neural networks. In this study, we proposed both semi-supervised and unsupervised methods and compared the performances between the supervised model and them. The neural networks were trained and tested on two well-known datasets: KITTI Dataset and EuRoC MAV Dataset.","PeriodicalId":274566,"journal":{"name":"2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128827170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Non-Verbal Behavior Generation for Virtual Characters in Group Conversations 群聊虚拟角色的非语言行为生成

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00016

Ferdinand de Coninck, Zerrin Yumak, G. Sandino, R. Veltkamp

引用次数: 9

Live Emoji: A Live Storytelling VR System with Programmable Cartoon-Style Emotion Embodiment 现场表情符号:一个具有可编程卡通风格情感体现的现场讲故事VR系统

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00057

Zhenjie Zhao, Feng Han, Xiaojuan Ma

引用次数: 3

An Affective Computing in Virtual Reality Environments for Managing Surgical Pain and Anxiety 在虚拟现实环境中的情感计算管理手术疼痛和焦虑

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00049

Vishnunarayan Girishan Prabhu, Courtney Linder, L. Stanley, Robert Morgan

{"title":"An Affective Computing in Virtual Reality Environments for Managing Surgical Pain and Anxiety","authors":"Vishnunarayan Girishan Prabhu, Courtney Linder, L. Stanley, Robert Morgan","doi":"10.1109/AIVR46125.2019.00049","DOIUrl":"https://doi.org/10.1109/AIVR46125.2019.00049","url":null,"abstract":"Pain and anxiety are common accompaniments of surgery. About 90% of people indicate elevated levels of anxiety during pre-operative care, and 66% of the people report moderate to high levels of pain immediately after surgery. Currently, opioids are the primary method for pain management during postoperative care, and approximately one in 16 surgical patients prescribed opioids becomes a long-term user. This, along with the current opioid epidemic crisis calls for alternative pain management mechanisms. This research focuses on utilizing affective computing techniques to develop and deliver an adaptive virtual reality experience based on the user's physiological response to reduce pain and anxiety. Biofeedback is integrated with a virtual environment utilizing the user's heart rate variability, respiration, and electrodermal activity. Early results from Total Knee Arthroplasty patients undergoing surgery at Patewood Memorial Hospital in Greenville, SC demonstrate promising results in the management of pain and anxiety during pre and post-operative care.","PeriodicalId":274566,"journal":{"name":"2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123100857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 6

Remote Environment Exploration with Drone Agent and Haptic Force Feedback 基于无人机代理和触觉力反馈的远程环境探测

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00034

Tinglin Duan, Parinya Punpongsanon, Shengxin Jia, D. Iwai, Kosuke Sato, K. Plataniotis

{"title":"Remote Environment Exploration with Drone Agent and Haptic Force Feedback","authors":"Tinglin Duan, Parinya Punpongsanon, Shengxin Jia, D. Iwai, Kosuke Sato, K. Plataniotis","doi":"10.1109/AIVR46125.2019.00034","DOIUrl":"https://doi.org/10.1109/AIVR46125.2019.00034","url":null,"abstract":"Camera drones allow exploring remote scenes that are inaccessible or inappropriate to visit in person. However, these exploration experiences are often limited due to insufficient scene information provided by front cameras, where only 2D images or videos are supplied. Combining a camera drone vision with haptic feedback would augment users' spatial understandings of the remote environment. But such designs are usually difficult for users to learn and apply, due to the complexity of the system and unfluent UAV control. In this paper, we present a new telepresence system for remote environment exploration, with a drone agent controlled by a VR mid-air panel. The drone is capable of generating real-time location and landmark details using integrated Simultaneous Location and Mapping (SLAM). The SLAMs' point cloud generations are produced using RGB input, and the results are passed to a Generative Adversarial Network (GAN) to reconstruct 3D remote scenes in real-time. The reconstructed objects are taken advantage of by haptic devices which could improve user experience through haptic rendering. Capable of providing both visual and haptic feedback, our system allows users to examine and exploit remote areas without having to be physically present. An experiment has been conducted to verify the usability of 3D reconstruction result in haptic feedback rendering.","PeriodicalId":274566,"journal":{"name":"2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115799403","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Structuring and Inspecting 3D Anchors for Seismic Volume into Hyperknowledge Base in Virtual Reality 虚拟现实超知识库中地震体三维锚的构造与检测

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00063

W. Santos, Isabela Chambers, E. V. Brazil, M. Moreno

{"title":"Structuring and Inspecting 3D Anchors for Seismic Volume into Hyperknowledge Base in Virtual Reality","authors":"W. Santos, Isabela Chambers, E. V. Brazil, M. Moreno","doi":"10.1109/AIVR46125.2019.00063","DOIUrl":"https://doi.org/10.1109/AIVR46125.2019.00063","url":null,"abstract":"Seismic data is a source of information geoscientists use to investigate underground regions to look for resources to explore. Such data are volumetric and noisy, and thus challenging to visualize, which motivated the research of new computational systems to assist the expert, such as visualization methods, signal processing, and machine learning models. We propose a system that aids geologists, geophysicists, and related experts in the domain in interpreting seismic data in virtual reality (VR). The system uses a hyperknowledge base (HKBase), which structures regions of interest (ROIs) as anchors with semantics from the user to the system and vice-versa. For instance, through the HKBase, the user can load and inspect the output from AI systems or give new inputs and feedback in the same way. We ran tests with experts to evaluate the system in their tasks to collect feedback and new insights on how the software could transform their routines. In accordance with our results, we claim we took one step forward for VR in the oil & gas industry by creating a valuable experience in the task of seismic interpretation.","PeriodicalId":274566,"journal":{"name":"2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115858030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Extracting Specific Voice from Mixed Audio Source 从混合音频源中提取特定的声音

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00039

Kunihiko Sato

引用次数: 0

Crowd and Procession Hypothesis Testing for Large-Scale Archaeological Sites 大型考古遗址的人群与队伍假设检验

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00069

Kristin Chow, Aline Normoyle, Jeanette Nicewinter, Clark L. Erickson, N. Badler

引用次数: 2

Vibration Feedback Controlled by Intuitive Pressing in Virtual Reality 虚拟现实中直观按压控制的振动反馈

2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2019-12-01 DOI: 10.1109/AIVR46125.2019.00041

Yu-Wei Wang, Tse-Yu Pan, Yung-Ju Chang, Min-Chun Hu

引用次数: 1