Child or Adult? Inferring Smartphone Users’ Age Group from Touch Measurements Alone

Abstract : We present a technique that classifies users’ age group, i.e., child or adult, from touch coordinates captured on touch-screen devices. Our technique delivered 86.5 % accuracy (user-independent) on a dataset of 119 participants (89 children ages 3 to 6) when classifying each touch event one at a time and up to 99 % accuracy when using a window of 7+ consecutive touches. Our results establish that it is possible to reliably classify a smartphone user on the fly as a child or an adult with high accuracy using only basic data about their touches, and will inform new, automatically adaptive interfaces for touch-screen devices.
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Communication dans un congrès
15th Human-Computer Interaction (INTERACT), Sep 2015, Bamberg, Germany. Lecture Notes in Computer Science, LNCS-9299 (Part IV), pp.1-9, 2015, Human-Computer Interaction – INTERACT 2015. 〈10.1007/978-3-319-22723-8_1〉
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https://hal.inria.fr/hal-01610821
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Soumis le : jeudi 5 octobre 2017 - 09:58:36
Dernière modification le : jeudi 5 octobre 2017 - 10:04:25

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Radu-Daniel Vatavu, Lisa Anthony, Quincy Brown. Child or Adult? Inferring Smartphone Users’ Age Group from Touch Measurements Alone. 15th Human-Computer Interaction (INTERACT), Sep 2015, Bamberg, Germany. Lecture Notes in Computer Science, LNCS-9299 (Part IV), pp.1-9, 2015, Human-Computer Interaction – INTERACT 2015. 〈10.1007/978-3-319-22723-8_1〉. 〈hal-01610821〉

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