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Guy Lüthi

dblp:332/0581 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Interaction techniques and input · 61% Wearable and physiological sensing · 30% Haptics and multimodal interaction · 9%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing
inertial sensing
0.612022
DeltaPen: A Device with Integrated High-Precision Translation and Rotation Sensing on Passive Surfaces · UIST 2022
Interaction techniques and input
pen input
0.612022
DeltaPen: A Device with Integrated High-Precision Translation and Rotation Sensing on Passive Surfaces · UIST 2022
Interaction techniques and input › gesture input
tilt-based interaction
0.612022
DeltaPen: A Device with Integrated High-Precision Translation and Rotation Sensing on Passive Surfaces · UIST 2022
Haptics and multimodal interaction
haptic actuator
0.212022
DeltaPen: A Device with Integrated High-Precision Translation and Rotation Sensing on Passive Surfaces · UIST 2022

Methods — techniques the papers use, named apart from their topics

pressure sensing · 0.6optical flow · 0.6inertial sensing · 0.6
YearPublicationVenuePosition
2022 DeltaPen: A Device with Integrated High-Precision Translation and Rotation Sensing on Passive Surfaces
abstract
We present DeltaPen, a pen device that operates on passive surfaces without the need for external tracking systems or active sensing surfaces. DeltaPen integrates two adjacent lens-less optical flow sensors at its tip, from which it reconstructs accurate directional motion as well as yaw rotation. DeltaPen also supports tilt interaction using a built-in inertial sensor. A pressure sensor and high-fidelity haptic actuator complements our pen device while retaining a compact form factor that supports mobile use on uninstrumented surfaces. We present a processing pipeline that reliably extracts fine-grained pen translations and rotations from the two optical flow sensors. To asses the accuracy of our translation and angle estimation pipeline, we conducted a technical evaluation in which we compared our approach with ground-truth measurements of participants’ pen movements during typical pen interactions. We conclude with several example applications that leverage our device’s capabilities. Taken together, we demonstrate novel input dimensions with DeltaPen that have so far only existed in systems that require active sensing surfaces or external tracking.
Guy Lüthi, Andreas Rene Fender, Christian Holz 0001
UIST1