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

Touch sensing on ad-hoc surfaces has the potential to transform everyday surfaces in the environment - desks, tables and walls - into tactile, touch-interactive surfaces, creating large, comfortable interactive spaces without the cost of large touch sensors. Depth sensors are a promising way to provide touch sensing on arbitrary surfaces, but past systems have suffered from high latency and poor touch detection accuracy. We apply a novel state machine-based approach to analyzing touch events, combined with a machine-learning approach to predictively classify touch events from depth data with lower latency and higher touch accuracy than previous approaches. Our system can reduce end-to-end touch latency to under 70ms, comparable to conventional capacitive touchscreens. Additionally, we open-source our dataset of over 30,000 touch events recorded in depth, infrared and RGB for the benefit of future researchers.

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