Interactive context-aware furniture recommendation using mixed reality

Hongfei Yu, Wei Liang, Shihao Song, Bing Ning*, Yixin Zhu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

We present a Mixed Reality (MR) system, through Hololens, to provide context-aware furniture recommendation in an interactive fashion. Firstly, a ranking-based metric learning method is adopted to represent the furniture compatibility through a latent space. Then, in the recommendation process, a physical scene is captured by the cameras mounted on the MR device, and two types of scene context are analyzed: (1) category context; (2) spatial context. At last, the one with the minimal weighted ranking distance in the latent space is recommended to the user. With MR devices, a user could perceive and manipulate the recommended furniture in real-time. We conduct user study to validate the efficacy of the proposed system.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages450-451
Number of pages2
ISBN (Electronic)9780738113678
DOIs
Publication statusPublished - Mar 2021
Event2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2021 - Virtual, Lisbon, Portugal
Duration: 27 Mar 20213 Apr 2021

Publication series

NameProceedings - 2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2021

Conference

Conference2021 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2021
Country/TerritoryPortugal
CityVirtual, Lisbon
Period27/03/213/04/21

Keywords

  • Furniture recommendation
  • Human computer interaction (HCI)
  • Human-centered computing
  • Interaction techniques; Human-centered computing
  • Recommendation system

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