Reducing Touchscreen Latency with Inertial Measurement Units
PredicTouch is a system that reduces touchscreen latency using neural networks and inertial measurement units (IMU) attached to positions such as the finger, wrist, and the stylus. An evaluation study showed that PredicTouch improves the throughput by 15% for finger input and 17% for input with a stylus. This work was presented at the ACM International Conference on Interactive Surfaces and Spaces (ISS ’17) in Brighton, UK in October 2017.
Publication
PredicTouch: A System to Reduce Touchscreen Latency Using Neural Networks and Inertial Measurement Units.
Huy Viet Le, Valentin Schwind, Philipp Göttlich, and Niels Henze. 2017. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (ISS '17). ACM, Brighton, United Kingdom.
Huy Viet Le, Valentin Schwind, Philipp Göttlich, and Niels Henze. 2017. In Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces (ISS '17). ACM, Brighton, United Kingdom.
@inproceedings{le2017predictouch,
author = {Le, Huy Viet and Schwind, Valentin and G\"{o}ttlich, Philipp and Henze, Niels},
title = {PredicTouch: A System to Reduce Touchscreen Latency Using Neural Networks and Inertial Measurement Units},
booktitle = {Proceedings of the 2017 ACM International Conference on Interactive Surfaces and Spaces},
series = {ISS '17},
year = {2017},
isbn = {978-1-4503-4691-7},
location = {Brighton, United Kingdom},
pages = {230--239},
numpages = {10},
url = {http://doi.acm.org/10.1145/3132272.3134138},
doi = {10.1145/3132272.3134138},
acmid = {3134138},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {IMU, Latency, lag, neural network, prediction, touch input},
}