Optimizing Product Placement for Virtual Stores

Wei Liang*, Luhui Wang, Xinzhe Yu, Changyang Li, Rawan Alghofaili, Yining Lang, Lap Fai Yu

*Corresponding author for this work

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

2 Citations (Scopus)

Abstract

The recent popularity of consumer-grade virtual reality devices has enabled users to experience immersive shopping in virtual environments. As in a real-world store, the placement of products in a virtual store should appeal to shoppers, which could be time-consuming, tedious, and non-trivial to create manually. Thus, this work introduces a novel approach for automatically optimizing product placement in virtual stores. Our approach considers product exposure and spatial constraints, applying an optimizer to search for optimal product placement solutions. We conducted qualitative scene rationality and quantitative product exposure experiments to validate our approach with users. The results show that the proposed approach can synthesize reasonable product placements and increase product exposures for different virtual stores.

Original languageEnglish
Title of host publicationProceedings - 2023 IEEE Conference Virtual Reality and 3D User Interfaces, VR 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages336-346
Number of pages11
ISBN (Electronic)9798350348156
DOIs
Publication statusPublished - 2023
Event30th IEEE Conference Virtual Reality and 3D User Interfaces, VR 2023 - Virtual, Online, China
Duration: 25 Mar 202329 Mar 2023

Publication series

NameProceedings - 2023 IEEE Conference Virtual Reality and 3D User Interfaces, VR 2023

Conference

Conference30th IEEE Conference Virtual Reality and 3D User Interfaces, VR 2023
Country/TerritoryChina
CityVirtual, Online
Period25/03/2329/03/23

Keywords

  • -Computing methodologies-Virtual reality
  • Human-centered computing-Human computer interaction (HCI)-

Fingerprint

Dive into the research topics of 'Optimizing Product Placement for Virtual Stores'. Together they form a unique fingerprint.

Cite this