ACM ISS 2022
Sun 20 - Thu 24 November 2022 Wellington, New Zealand

We propose a method that predicts the success rate in pointing to 2D rectangular targets by using 1D vertical-bar and horizontal-bar task results. The method can predict the success rates for more practical situations under fewer experimental conditions. This shortens the duration of experiments, thus saving costs for researchers and practitioners. We verified the method through two experiments: laboratory-based and crowdsourced ones. In the laboratory-based experiment, we found that using 1D task results to predict the success rate for 2D targets slightly decreases the prediction accuracy. In the crowdsourced experiment, this method scored better than using 2D task results. Thus, we recommend that researchers use the method properly depending on the situation.

Mon 21 Nov

Displayed time zone: Auckland, Wellington change

13:30 - 15:00
Session 2: TouchPapers at Rutherford House Lecture Theatre 2
Chair(s): Hans Christian Jetter University of Lübeck
13:30
22m
Talk
Theoretically-Defined vs. User-Defined Squeeze Gestures
Papers
Santiago Villarreal-Narvaez Université catholique de Louvain, Arthur Sluÿters Université catholique de Louvain, Jean Vanderdonckt Université catholique de Louvain, Efrem MBAKI LUZAYISU University of Kinshasa
DOI Media Attached
13:52
22m
Talk
Predicting Touch Accuracy for Rectangular Targets by Using One-Dimensional Task Results
Papers
A: Hiroki Usuba Yahoo, A: Shota Yamanaka Yahoo, A: Junichi Sato Yahoo Japan Corporation, A: Homei Miyashita Meiji University
DOI Media Attached
14:15
22m
Talk
The Effectiveness of Path-Segmentation for Modeling Lasso Times in Width-Varying Paths
Papers
Shota Yamanaka Yahoo, Hiroki Usuba Yahoo, Wolfgang Stuerzlinger Simon Fraser University, Homei Miyashita Meiji University
DOI Media Attached
14:37
22m
Talk
Reducing the Latency of Touch Tracking on Ad-hoc Surfaces
Papers
Xu Fan , Robert Xiao University of British Columbia
DOI Media Attached