Reducing Latency with a Continuous Prediction:
Latency in direct-touch systems creates a spatial gap between the finger and the digital object when dragging. This breaks the illusion of presence, and has a negative effect on users' performances in common tasks such as target acquisitions. Latency can be reduced with faster hardware, but reaching imperceptible levels of latency with a hardware-only approach is a difficult challenge and an energy inefficient solution. We studied the use of a continuous prediction of the touch location as an alternative to the hardware only approach to reduce the latency gap. We implemented a low latency touch surface and experimented with a constant speed linear prediction with various system latencies in the range [25ms-75ms]. We ran a user experiment to objectively assess the benefits of the prediction on users' performances in target acquisition tasks. Our study reveals that the prediction length is strongly constrained by the nature of target acquisition tasks, but that the approach can be successfully applied to counteract a large part of the negative effect of latency on users' performances.
This work was partially funded by the French government in the LabEx PERSYVAL-Lab (ANR-11-LABX-0025-01).