TY - GEN
T1 - PredicTaps
T2 - 2020 ACM CHI Conference on Human Factors in Computing Systems, CHI EA 2020
AU - Ikematsu, Kaori
AU - Tsubouchi, Kota
AU - Yamanaka, Shota
N1 - Publisher Copyright:
© 2020 Owner/Author.
PY - 2020/4/25
Y1 - 2020/4/25
N2 - In general, a system with touch input waits for a certain period of time (typically 350 - 500 ms) for a subsequent tap to determine whether the initial tap was a single tap or the first tap of a double tap. This results in latency of hundreds of milliseconds for a single-tap event. To reduce the latency, we propose a novel machine-learning-based tap recognition method called "PredicTaps". In the PredicTaps method, by using touch-event data gathered from the capacitive touch surface, the system immediately predicts whether a detected tap is a single tap or the first tap of a double tap. Then, in accordance with the prediction, the system determines whether to execute a single-tap event immediately or wait for a subsequent second tap. This paper reports the feasibility study of PredicTaps.
AB - In general, a system with touch input waits for a certain period of time (typically 350 - 500 ms) for a subsequent tap to determine whether the initial tap was a single tap or the first tap of a double tap. This results in latency of hundreds of milliseconds for a single-tap event. To reduce the latency, we propose a novel machine-learning-based tap recognition method called "PredicTaps". In the PredicTaps method, by using touch-event data gathered from the capacitive touch surface, the system immediately predicts whether a detected tap is a single tap or the first tap of a double tap. Then, in accordance with the prediction, the system determines whether to execute a single-tap event immediately or wait for a subsequent second tap. This paper reports the feasibility study of PredicTaps.
KW - Double-tap
KW - Latency
KW - Single-tap
KW - Touch inputs
UR - http://www.scopus.com/inward/record.url?scp=85090234754&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85090234754&partnerID=8YFLogxK
U2 - 10.1145/3334480.3382933
DO - 10.1145/3334480.3382933
M3 - Conference contribution
AN - SCOPUS:85090234754
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI EA 2020 - Extended Abstracts of the 2020 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 25 April 2020 through 30 April 2020
ER -