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Virtual Reality Aided High-Quality 3D Reconstruction by Remote Drones
Zhang, DI1; Xu, Feng2; Pun, Chi Man3; Yang, Yang1; Lan, Rushi4; Wang, Liejun5; Li, Yujie6; Gao, Hao5
2022-02-01
Source PublicationACM Transactions on Internet Technology
ISSN1533-5399
Volume22Issue:1
Abstract

Artificial intelligence including deep learning and 3D reconstruction methods is changing the daily life of people. Now, an unmanned aerial vehicle that can move freely in the air and avoid harsh ground conditions has been commonly adopted as a suitable tool for 3D reconstruction. The traditional 3D reconstruction mission based on drones usually consists of two steps: image collection and offline post-processing. But there are two problems: one is the uncertainty of whether all parts of the target object are covered, and another is the tedious post-processing time. Inspired by modern deep learning methods, we build a telexistence drone system with an onboard deep learning computation module and a wireless data transmission module that perform incremental real-time dense reconstruction of urban cities by itself. Two technical contributions are proposed to solve the preceding issues. First, based on the popular depth fusion surface reconstruction framework, we combine it with a visual-inertial odometry estimator that integrates the inertial measurement unit and allows for robust camera tracking as well as high-accuracy online 3D scan. Second, the capability of real-time 3D reconstruction enables a new rendering technique that can visualize the reconstructed geometry of the target as navigation guidance in the HMD. Therefore, it turns the traditional path-planning-based modeling process into an interactive one, leading to a higher level of scan completeness. The experiments in the simulation system and our real prototype demonstrate an improved quality of the 3D model using our artificial intelligence leveraged drone system.

Keyword3d Reconstruction Human-robot-interaction Telexistence Unmanned Aerial Vehicle Virtual Reality
DOI10.1145/3458930
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Software Engineering
WOS IDWOS:000717399100018
Scopus ID2-s2.0-85119199966
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Citation statistics
Cited Times [WOS]:1   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Corresponding AuthorZhang, DI
Affiliation1.Nanjing University of Posts and Telecommunications, Nanjing, China
2.Tsinghua University, Beijing, China
3.University of Macau, Taipa, Macao
4.Guilin University of Electronic Technology, Guilin, China
5.Xinjiang University, Ürümqi, China
6.Fukuoka University, Kitakyushu City, Japan
Recommended Citation
GB/T 7714
Zhang, DI,Xu, Feng,Pun, Chi Man,et al. Virtual Reality Aided High-Quality 3D Reconstruction by Remote Drones[J]. ACM Transactions on Internet Technology,2022,22(1).
APA Zhang, DI,Xu, Feng,Pun, Chi Man,Yang, Yang,Lan, Rushi,Wang, Liejun,Li, Yujie,&Gao, Hao.(2022).Virtual Reality Aided High-Quality 3D Reconstruction by Remote Drones.ACM Transactions on Internet Technology,22(1).
MLA Zhang, DI,et al."Virtual Reality Aided High-Quality 3D Reconstruction by Remote Drones".ACM Transactions on Internet Technology 22.1(2022).
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