An adaptive FIR filter for trajectory prediction and latency reduction in direct Human–Computer interactions. (October 2019) - Aranovskiy, S.; Ushirobira, R.; Efimov, D.; Casiez, G.
Abstract: The problem of latency reduction in direct Human–Computer interactions is considered. The proposed method is based on a frequency-domain approximation of a non-causal ideal predictor with a finite impulse response filter. Given a sufficiently rich dataset, the parameters of the filter can be either optimized off-line or tuned on-line with the proposed adaptive algorithm. The performance of the proposed solution is evaluated in an experimental study consisting of drawings on a touchscreen. Highlights: Latency reduction is presented as the trajectory prediction problem. Finite Impulse Response (FIR) filters are used for trajectory prediction. Experimental studies show that adaptive FIR outperforms standard approaches.