AutoGain: Gain Function Adaptation with ...
Type de document :
Communication dans un congrès avec actes
DOI :
Titre :
AutoGain: Gain Function Adaptation with Submovement Efficiency Optimization
Auteur(s) :
Lee, Byungjoo [Auteur]
Korea Advanced Institute of Science and Technology [KAIST]
Nancel, Mathieu [Auteur]
Technology and knowledge for interaction [LOKI]
Kim, Sunjun [Auteur]
Korea Advanced Institute of Science and Technology [KAIST]
Oulasvirta, Antti [Auteur]
Aalto University
Korea Advanced Institute of Science and Technology [KAIST]
Nancel, Mathieu [Auteur]
Technology and knowledge for interaction [LOKI]
Kim, Sunjun [Auteur]
Korea Advanced Institute of Science and Technology [KAIST]
Oulasvirta, Antti [Auteur]
Aalto University
Titre de la manifestation scientifique :
Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems (CHI '20)
Ville :
Honolulu
Pays :
Etats-Unis d'Amérique
Date de début de la manifestation scientifique :
2020-04-25
Éditeur :
ACM
Date de publication :
2020-04-25
Mot(s)-clé(s) en anglais :
Pointing
Submovement
CD gain functions
Pointer acceleration
Human Performance
Pointing facilitation
Submovement
CD gain functions
Pointer acceleration
Human Performance
Pointing facilitation
Discipline(s) HAL :
Informatique [cs]/Interface homme-machine [cs.HC]
Résumé en anglais : [en]
A well-designed control-to-display gain function can improve pointing performance with indirect pointing devices like track-pads. However, the design of gain functions is challenging and mostly based on trial and error. ...
Lire la suite >A well-designed control-to-display gain function can improve pointing performance with indirect pointing devices like track-pads. However, the design of gain functions is challenging and mostly based on trial and error. AutoGain is a novel method to individualize a gain function for indirect pointing devices in contexts where cursor trajectories can be tracked. It gradually improves pointing efficiency by using a novel submovement-level tracking+optimization technique that minimizes aiming error (undershooting/overshooting) for each submovement. We first show that AutoGain can produce, from scratch, gain functions with performance comparable to commercial designs, in less than a half-hour of active use. Second, we demonstrate AutoGain's applicability to emerging input devices (here, a Leap Motion controller) with no reference gain functions. Third, a one-month longitudinal study of normal computer use with AutoGain showed performance improvements from participants' default functions.Lire moins >
Lire la suite >A well-designed control-to-display gain function can improve pointing performance with indirect pointing devices like track-pads. However, the design of gain functions is challenging and mostly based on trial and error. AutoGain is a novel method to individualize a gain function for indirect pointing devices in contexts where cursor trajectories can be tracked. It gradually improves pointing efficiency by using a novel submovement-level tracking+optimization technique that minimizes aiming error (undershooting/overshooting) for each submovement. We first show that AutoGain can produce, from scratch, gain functions with performance comparable to commercial designs, in less than a half-hour of active use. Second, we demonstrate AutoGain's applicability to emerging input devices (here, a Leap Motion controller) with no reference gain functions. Third, a one-month longitudinal study of normal computer use with AutoGain showed performance improvements from participants' default functions.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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- https://hal.inria.fr/hal-02918581/document
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- http://arxiv.org/pdf/1611.08154
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- CHI2020_AutoGain.pdf
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- 1611.08154
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