TurboTouch predictor Python version

Provides a Python implementation for the TurboTouch predictor.

Install

pip install TurboTouchPredictor --upgrade

Minimal example

from TurboTouchPredictor import TurboTouchPredictor

ttpPredictor = TurboTouchPredictor();

// Amount of prediction in ms. Allowed values: 0, 16, 32, 48, 64
ttpPredictor.setAmountOfCompensation(32);

predictedPoint = ttpPredictor.predict(0, 0, 0, "Interacting") # x, y, t, state

Doc

Related publication

@inproceedings{10.1145/3242587.3242646,
    author = {Nancel, Mathieu and Aranovskiy, Stanislav and Ushirobira, Rosane and Efimov, Denis and Poulmane, Sebastien and Roussel, Nicolas and Casiez, G\'{e}ry},
    title = {Next-Point Prediction for Direct Touch Using Finite-Time Derivative Estimation},
    year = {2018},
    isbn = {9781450359481},
    publisher = {Association for Computing Machinery},
    address = {New York, NY, USA},
    url = {https://doi.org/10.1145/3242587.3242646},
    doi = {10.1145/3242587.3242646},
    abstract = {End-to-end latency in interactive systems is detrimental to performance and usability, and comes from a combination of hardware and software delays. While these delays are steadily addressed by hardware and software improvements, it is at a decelerating pace. In parallel, short-term input prediction has shown promising results in recent years, in both research and industry, as an addition to these efforts. We describe a new prediction algorithm for direct touch devices based on (i) a state-of-the-art finite-time derivative estimator, (ii) a smoothing mechanism based on input speed, and (iii) a post-filtering of the prediction in two steps. Using both a pre-existing dataset of touch input as benchmark, and subjective data from a new user study, we show that this new predictor outperforms the predictors currently available in the literature and industry, based on metrics that model user-defined negative side-effects caused by input prediction. In particular, we show that our predictor can predict up to 2 or 3 times further than existing techniques with minimal negative side-effects.},
    booktitle = {Proceedings of the 31st Annual ACM Symposium on User Interface Software and Technology},
    pages = {793–807},
    numpages = {15},
    keywords = {touch input, latency, lag, prediction technique},
    location = {Berlin, Germany},
    series = {UIST '18}
}