DeepMix: A real-time adaptive virtual content registration system with intelligent detection

Yongjie Guan, Xueyu Hou, Tao Han, Sheng Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

This demo proposes a novel virtual content registration system (DeepMix) for MR applications, which integrates state-of-the-art computer vision technology and allows real-time interaction between virtual contents and arbitrary real objects in the physical environment for MR devices. DeepMix effectively utilizes different sensors on MR devices to measure the dimension and spatial location of real objects in the physical environment and improves the quality of experience (QoE) of users adaptively under various situations. Compared with state-of-the-art virtual content registration methods, DeepMix is a light-weight registration system with more flexibility, higher intelligence, and stronger adaptability.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665404433
DOIs
StatePublished - May 10 2021
Externally publishedYes
Event2021 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021 - Virtual, Online
Duration: May 9 2021May 12 2021

Publication series

NameIEEE INFOCOM 2021 - IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021

Conference

Conference2021 IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 2021
CityVirtual, Online
Period5/9/215/12/21

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management
  • Safety, Risk, Reliability and Quality

Keywords

  • Mixed reality
  • Optical head-mounted display
  • Virtual content registration

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