2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)最新文献_第3页

DatAR: An Immersive Literature Exploration Environment for Neuroscientists 数据:神经科学家的沉浸式文献探索环境

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00020

Ivar Troost, Ghazaleh Tanhaei, L. Hardman, Wolfgang Hürst

引用次数: 2

Extended Abstract: CoShopper - Leveraging Artificial Intelligence for an Enhanced Augmented Reality Grocery Shopping Experience 扩展摘要:CoShopper -利用人工智能增强增强现实杂货店购物体验

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00069

Yasmeen Alhamdan, Saif Alabachi, N. Khan

引用次数: 3

MIXR: A Standard Architecture for Medical Image Analysis in Augmented and Mixed Reality MIXR:增强和混合现实中医学图像分析的标准体系结构

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00053

Benjamin Allison, Xujiong Ye, Faraz Janan

{"title":"MIXR: A Standard Architecture for Medical Image Analysis in Augmented and Mixed Reality","authors":"Benjamin Allison, Xujiong Ye, Faraz Janan","doi":"10.1109/AIVR50618.2020.00053","DOIUrl":"https://doi.org/10.1109/AIVR50618.2020.00053","url":null,"abstract":"Medical image analysis is evolving into a new dimension: where it will combine the power of AI and machine learning with real-time, real-space displays, namely Virtual Reality (VR), Augmented Reality (AR) and Mixed Reality (MR) - known collectively as Extended Reality (XR). These devices, typically available as head-mounted displays, are enabling the move towards the complete transformation of how medical data is viewed, processed and analysed in clinical practice. There have been recent attempts on how XR gadgets can help in surgical planning and training of medics. However, the radiological front from a detection, diagnostics and prognosis remains unexplored. In this paper we propose a standard framework or architecture called Medical Imaging in Extended Reality (MIXR) for building medical image analysis applications in XR. MIXR consists of several components used in literature; however, tied together for reconstructing volume data in 3D space. Our focus here is on the reconstruction mechanism for CT and MRI data in XR; nevertheless, the framework we propose has applications beyond these modalities.","PeriodicalId":348199,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116460022","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: 2

Interactive and Scalable Layout Synthesis with Design Templates 交互式和可伸缩布局合成与设计模板

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00049

Hameedullah Farooki, E. Cansizoglu, Jae-Woo Choi, Tomer Weiss

引用次数: 0

Attention Estimation in Virtual Reality with EEG based Image Regression 基于脑电图像回归的虚拟现实注意力估计

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00012

V. Delvigne, H. Wannous, Jean-Philippe Vandeborre, L. Ris, T. Dutoit

{"title":"Attention Estimation in Virtual Reality with EEG based Image Regression","authors":"V. Delvigne, H. Wannous, Jean-Philippe Vandeborre, L. Ris, T. Dutoit","doi":"10.1109/AIVR50618.2020.00012","DOIUrl":"https://doi.org/10.1109/AIVR50618.2020.00012","url":null,"abstract":"Attention Deficit Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder affecting a certain amount of children and their way of living. A novel method to treat this disorder is to use Brain-Computer Interfaces (BCI) throughout the patient learns to self-regulate his symptoms by herself. In this context, researches have led to tools aiming to estimate the attention toward these interfaces. In parallel, the democratization of virtual reality (VR) headset, and the fact that it produces valid environments for several aspects: safe, flexible and ecologically valid have led to an increase of its use for BCI application. Another point is that Artificial Intelligence (AI) is more and more developed in different domain among which medical application. In this paper, we present an innovative method aiming to estimate attention from the measurement of physiological signals: Electroencephalogram (EEG), gaze direction and head movement. This framework is developed to assess attention in VR environments. We propose a novel approach for feature extraction and a dedicated Machine Learning model. The pilot study has been applied on a set of volunteer and our approach presents a lower error rate in comparison with the state of the art methods.","PeriodicalId":348199,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130558763","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

Inverse Kinematics and Temporal Convolutional Networks for Sequential Pose Analysis in VR 基于逆运动学和时间卷积网络的VR序列姿态分析

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00056

David C. Jeong, Jackie Jingyi Xu, L. Miller

引用次数: 6

Problems with Physical Simulation in a Virtual Lego-based Assembly Task using Unity3D Engine 使用Unity3D引擎在虚拟乐高装配任务中的物理模拟问题

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00060

Nor Farzana Syaza Jeffri, D. R. A. Rambli

引用次数: 1

A QoE and Visual Attention Evaluation on the Influence of Spatial Audio in 360 Videos 360视频中空间音频影响的QoE和视觉注意力评价

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00071

Amit Hirway, Yuansong Qiao, Niall Murray

{"title":"A QoE and Visual Attention Evaluation on the Influence of Spatial Audio in 360 Videos","authors":"Amit Hirway, Yuansong Qiao, Niall Murray","doi":"10.1109/AIVR50618.2020.00071","DOIUrl":"https://doi.org/10.1109/AIVR50618.2020.00071","url":null,"abstract":"Recently, there has been growing interest from academia and industry on the application of immersive technologies across a range of domains. Once such technology, 360° video, can be captured using an omnidirectional multi-camera arrangement. These 360° videos can then be rendered via Virtual Reality (VR) Head Mounted Displays (HMD). Viewers then have the freedom to look around the scene in any direction they wish. Whereas a body of work exists that focused on modeling visual attention (VA) in VR, little research has considered the impact of the audio modality on VA in VR. It is well accepted that audio has an important role in VR experiences. High quality spatial audio offers listeners the opportunity to experience sound in all directions. One such technique, Ambisonics or 3D audio, offers a complete 360° soundscape. This paper reports the results of an empirical study that looked at understanding how (if at all) spatial audio influences visual attention in 360° videos. It also assessed the impact of spatial audio on the user’s Quality of Experience (QoE) by capturing implicit, explicit, and objective metrics. The results suggest surprisingly similar explicit QoE ratings for both the spatial and non-spatial audio environments. The implicit metrics indicate that users integrated with the spatial environment more quickly than the non-spatial environment. Users who experienced the spatial audio environment had a higher maximum mean head pose pitch value and were found to be more focused towards the sound-emitting regions in the spatial audio environment experiences.","PeriodicalId":348199,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127970191","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

An Immersive Node-Link Visualization of Artificial Neural Networks for Machine Learning Experts 面向机器学习专家的沉浸式节点-链接人工神经网络可视化

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00015

M. Bellgardt, C. Scheiderer, T. Kuhlen

引用次数: 4

Towards Computer Aided Diagnosis of Autism Spectrum Disorder Using Virtual Environments 利用虚拟环境进行自闭症谱系障碍的计算机辅助诊断

2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR) Pub Date : 2020-12-01 DOI: 10.1109/AIVR50618.2020.00029

Daniel Roth, M. Jording, Tobias Schmee, Peter Kullmann, N. Navab, K. Vogeley

{"title":"Towards Computer Aided Diagnosis of Autism Spectrum Disorder Using Virtual Environments","authors":"Daniel Roth, M. Jording, Tobias Schmee, Peter Kullmann, N. Navab, K. Vogeley","doi":"10.1109/AIVR50618.2020.00029","DOIUrl":"https://doi.org/10.1109/AIVR50618.2020.00029","url":null,"abstract":"Autism Spectrum Disorders (ASD) are neurodevelopmental disorders that are associated with characteristic difficulties to express and interpret nonverbal behavior, such as social gaze behavior. The state of the art in diagnosis is the clinical interview that is time intensive for the clinicians and does not take into account any objective measures of behavior. We herewith propose an empirical approach that can potentially support diagnosis based on the assessment of nonverbal behavior in avatar-mediated interactions in virtual environments. In a first study, ASD individuals and a typically developed control group were interacting in dyads. Head motion, and eye gaze of both interlocutors were recorded, replicated to the avatars and displayed to the partner through a distributed virtual environment. The nonverbal behavior of both interaction partners was recorded, and resulting preprocessed data was classified with up to 92.9parcent classification accuracy, with the amount of eye area focus and the average horizontal gaze change being the most relevant features. We expect that such systems could improve the diagnostic assessment on the basis of objective measures of nonverbal behavior.","PeriodicalId":348199,"journal":{"name":"2020 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126406853","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