@inproceedings{Le:2018:IFA,
 abstract = {Smartphones are the most successful mobile devices and offer intuitive interaction through touchscreens. Current devices treat all fingers equally and only sense touch contacts on the front of the device. In this paper, we present InfiniTouch, the first system that enables touch input on the whole device surface and identifies the fingers touching the device without external sensors while keeping the form factor of a standard smartphone. We first developed a prototype with capacitive sensors on the front, the back and on three sides. We then conducted a study to train a convolutional neural network that identifies fingers with an accuracy of 95.78% while estimating their position with a mean absolute error of 0.74cm. We demonstrate the usefulness of multiple use cases made possible with InfiniTouch, including finger-aware gestures and finger flexion state as an action modifier.},
 address = {New York, NY, USA},
 author = {Huy Viet Le and Sven Mayer and Niels Henze },
 booktitle = {Proceedings of the 31th Annual ACM Symposium on User Interface Software and Technology},
 date = {2018-10-14},
 doi = {10.1145/3242587.3242605},
 keywords = {machine learning, mobile device, touchscreen},
 publisher = {ACM},
 pubstate = {published},
 series = {UIST'18},
 title = {InfiniTouch: Finger-Aware Interaction on Fully Touch Sensitive Smartphones},
 tppubtype = {inproceedings},
 url = {http://sven-mayer.com/wp-content/uploads/2018/08/le2018infinitouch.pdf
https://github.com/interactionlab/InfiniTouch
https://www.youtube.com/watch?v=0XlF1kenRp8
https://www.youtube.com/watch?v=OvvZwMJCyVU},
 year = {2018}
}