DTP：学习从稀疏的虚拟现实传感器测量结果中实时估计全身姿势

IF 4.4 3区计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Virtual Reality Pub Date : 2024-05-23 DOI:10.1007/s10055-024-01011-1

Qiang Zeng, Gang Zheng, Qian Liu

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

DTP: learning to estimate full-body pose in real-time from sparse VR sensor measurements

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DTP: learning to estimate full-body pose in real-time from sparse VR sensor measurements

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来源期刊

Virtual Reality COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-COMPUTER SCIENCE, SOFTWARE ENGINEERING

CiteScore

8.30

自引率

14.30%

发文量

审稿时长

>12 weeks

期刊介绍： The journal, established in 1995, publishes original research in Virtual Reality, Augmented and Mixed Reality that shapes and informs the community. The multidisciplinary nature of the field means that submissions are welcomed on a wide range of topics including, but not limited to: Original research studies of Virtual Reality, Augmented Reality, Mixed Reality and real-time visualization applications Development and evaluation of systems, tools, techniques and software that advance the field, including: Display technologies, including Head Mounted Displays, simulators and immersive displays Haptic technologies, including novel devices, interaction and rendering Interaction management, including gesture control, eye gaze, biosensors and wearables Tracking technologies VR/AR/MR in medicine, including training, surgical simulation, rehabilitation, and tissue/organ modelling. Impactful and original applications and studies of VR/AR/MR’s utility in areas such as manufacturing, business, telecommunications, arts, education, design, entertainment and defence Research demonstrating new techniques and approaches to designing, building and evaluating virtual and augmented reality systems Original research studies assessing the social, ethical, data or legal aspects of VR/AR/MR.