Toni Kuronen

Dr. Toni Kuronen


Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 March 2021 in Applied Energy
Verified
Journal Article
Open access
AMAleksei Mashlakov
Aleksei Mashlakov
TKToni Kuronen
Toni Kuronen
LLLasse Lensu
Lasse Lensu
AKArto Kaarna
Arto Kaarna
SHSamuli Honkapuro
Samuli Honkapuro

1 August 2017 in Chemical Engineering Science
Verified
Journal Article
Open access
JTJussi Tamminen
Jussi Tamminen
ELEsko Lahdenperä
Esko Lahdenperä
TKTuomas Koiranen
Tuomas Koiranen
TKToni Kuronen
Toni Kuronen
TETuomas Eerola
Tuomas Eerola
HKHeikki Kälviäinen
Heikki Kälviäinen

9 June 2015
Verified
Book Chapter
Closed access
PDF file
TKToni Kuronen
Toni Kuronen
TETuomas Eerola
Tuomas Eerola
LLLasse Lensu
Lasse Lensu
JTJari Takatalo
Jari Takatalo
JHJukka Häkkinen
Jukka Häkkinen
HKHeikki Kälviäinen
Heikki Kälviäinen

23 November 2017
Verified
Book Chapter
Closed access
PDF file
VLVadim Lyubanenko
Vadim Lyubanenko
TKToni Kuronen
Toni Kuronen
TETuomas Eerola
Tuomas Eerola
LLLasse Lensu
Lasse Lensu
HKHeikki Kälviäinen
Heikki Kälviäinen
JHJukka Häkkinen
Jukka Häkkinen

25 September 2018
Verified
Book Chapter
Closed access
PDF file
TKToni Kuronen
Toni Kuronen
TETuomas Eerola
Tuomas Eerola
LLLasse Lensu
Lasse Lensu
HKHeikki Kälviäinen
Heikki Kälviäinen

30 November 2019
Verified
Book Chapter
Open access
PDF file
TKToni Kuronen
Toni Kuronen
TETuomas Eerola
Tuomas Eerola
LLLasse Lensu
Lasse Lensu
JHJukka Häkkinen
Jukka Häkkinen
HKHeikki Kälviäinen
Heikki Kälviäinen
In order to develop better touch and gesture user interfaces, it is important to be able to measure how humans move their hands while interacting with technical devices. The recent advances in high-speed imaging technology and in image-based object tracking techniques have made it possible to accurately measure the hand movement from videos without the need for data gloves or other sensors that would limit the natural hand movements. In this paper, we propose a complete framework to measure hand movements in 3D in human-computer interaction situations. The framework includes the composition of the measurement setup, selecting the object tracking methods, post-processing of the motion trajectories, 3D trajectory reconstruction, and characterizing and visualizing the movement data. We demonstrate the framework in a context where 3D touch screen usability is studied with 3D stimuli.