Frequency domain forecasting approach for latency reduction in direct human-computer interaction

Abstract

Abstract-The problem of latency reduction in direct humancomputer interaction is considered and formulated as a trajectory prediction problem. To solve the problem, the predictor is constructed as a frequency-domain approximation of the noncasual ideal predictor. This approximation can be computed analytically, or obtained as an optimization task. An adaptive modification of the forecasting algorithm is proposed taking into account possible variations in user behavior. Experimental results illustrate the applicability of the proposed solution.

An adaptive FIR filter for trajectory prediction and latency reduction in direct Human–Computer interactions

“…Experimental results illustrate the applicability of the proposed forecasting algorithm and its performance compared to other methods. Preliminary results of this study were reported in Aranovskiy et al (2017b). Extending that work, this manuscript contains i) the proof of the forecasting accuracy bound (15), see Proposition 1, ii) the detailed description of the experimental setup and iii) comparison to the methods currently available in patents Moussavi (2014) and Qingkui (2014).…”

Next-Point Prediction for Direct Touch Using Finite-Time Derivative Estimation

“…Another approach based on finite impulse response (FIR) filters has been proposed recently in [2]. It demonstrates good robustness properties with respect to measurement noise, but still requires more computational capacities (involves matrix manipulations with 16 times 16 matrices for both X and Y) without a corresponding quality of differentiation improvement comparing to HOM differentiator.…”

“…The calculations that follow are described for the x coordinate only for simplicity, and must be performed for y as well in real use 2. Our prediction algorithm and tuning process are available at ns.inria.fr/loki/TTp/.…”