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Enabling hand-crafted visual markers at scale

Preston, William; Benford, Steve; Thorn, Emily-Clare; Koleva, Boriana; Rennick-Egglestone, Stefan; Mortier, Richard; Quinn, Anthony; Stell, John; Worboys, Michael

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Authors

William Preston

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STEVE BENFORD steve.benford@nottingham.ac.uk
Dunford Chair in Computer Science

EMILY THORN EMILY.THORN@NOTTINGHAM.AC.UK
Research Assistant

Richard Mortier

Anthony Quinn

John Stell

Michael Worboys



Abstract

As locative media and augmented reality spread into the everyday world so it becomes important to create aesthetic visual markers at scale. We explore a designer-centred approach in which skilled designers handcraft seed designs that are automatically recombined to create many markers as subtle variants of a common theme. First, we extend the d-touch topological approach to creating visual markers that has previously been shown to support creative design with two new techniques: area order codes and visual checksums. We then show how the topological structure of such markers provides the basis for recombining designs to generate many variations. We demonstrate our approach through the creation of beautiful, personalized and interactive wallpaper. We reflect on how technologies must enable designers to balance goals of scalability, aesthetics and reliability in creating beautiful interactive decoration.

Citation

Preston, W., Benford, S., Thorn, E., Koleva, B., Rennick-Egglestone, S., Mortier, R., …Worboys, M. (2017). Enabling hand-crafted visual markers at scale. . https://doi.org/10.1145/3064663.3064746

Conference Name ACM SIGCHI Conference on Designing Interactive Systems (DIS '17)
Start Date Jun 10, 2017
End Date Jun 14, 2017
Acceptance Date Mar 13, 2017
Publication Date Jun 14, 2017
Deposit Date Apr 12, 2017
Publicly Available Date Jun 14, 2017
Publisher Association for Computing Machinery (ACM)
Peer Reviewed Peer Reviewed
Pages 1227-1237
ISBN 978-1-4503-4922-2
DOI https://doi.org/10.1145/3064663.3064746
Keywords Visual markers, topological markers, fiducial markers, patterns, computer vision, image recognition
Public URL https://nottingham-repository.worktribe.com/output/866369

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