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  4. AuctentionAR -Auctioning Off Visual Attention in Mixed Reality
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AuctentionAR -Auctioning Off Visual Attention in Mixed Reality

Type
conference contribution
Date Issued
2024-05-11
Author(s)
Adrian Pandjaitan  
;
Jannis Rene Strecker  
;
Kenan Bektas  
;
Simon Mayer  
DOI
10.1145/3613905.3650941
Research Team
Interaction- and Communication-based Systems (https://interactions.ics.unisg.ch)
Abstract
Mixed Reality technologies are increasingly interwoven with our everyday lives. A variety of powerful Head Mounted Displays have recently entered consumer electronics markets, and more are under development, opening new dimensions for spatial computing. This development will likely not stop at the advertising industry either, as first forays into this area have already been made. We present AuctentionAR which allows users to sell off their visual attention to interested parties. It consists of a HoloLens 2, a remote server executing the auctioning logic, the YOLOv7 model for image recognition of products which may induce an advertising intent, and several bidders interested in advertising their products. As this system comes with substantial privacy implications, we discuss what needs to be considered in future implementation so as to make this system a basis for a privacy preserving MR advertising future.
Language
English (United States)
Keywords
visual attention
notifications
auctioning
object detection
augmented reality
innovation
advertisement
marketing
HSG Classification
contribution to scientific community
Refereed
Yes
Book title
Extended Abstracts of the CHI Conference on Human Factors in Computing Systems (CHI EA ’24)
Publisher
ACM
Publisher place
New York, NY, USA
Pages
6
Event Title
CHI Conference on Human Factors in Computing Systems (CHI'24)
Event Location
Honolulu, HI, USA
Event Date
May 11-16, 2024
Official URL
https://doi.org/10.1145/3613905.3650941
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/119777
Subject(s)

computer science

Division(s)

ICS - Institute of Co...

Contact Email Address
adrian.pandjaitan@student.unisg.ch
File(s)
Thumbnail Image

open.access

Name

Pandjaitan et al_2024_AuctentionAR.pdf

Size

2.19 MB

Format

Adobe PDF

Checksum (MD5)

7d48b365e7e69ef299f98d1fd4afa009

Support
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