Frequency Domain Forecasting Approach for Latency Reduction in Direct Human-Computer Interaction

Stanislav Aranovskiy 1 Rosane Ushirobira 2, 3 Denis Efimov 2, 3 Géry Casiez 4, 5
2 NON-A - Non-Asymptotic estimation for online systems
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
5 MJOLNIR - Computing tools to empower users
Inria Lille - Nord Europe, CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Abstract : The problem of latency reduction in direct human-computer 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 non-casual 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.
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Communication dans un congrès
CDC 2017 - 56th IEEE Conference on Decision and Control, Dec 2017, Melbourne, Australia. pp.1-6
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Soumis le : mardi 28 novembre 2017 - 22:30:34
Dernière modification le : jeudi 11 janvier 2018 - 06:27:32

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Stanislav Aranovskiy, Rosane Ushirobira, Denis Efimov, Géry Casiez. Frequency Domain Forecasting Approach for Latency Reduction in Direct Human-Computer Interaction. CDC 2017 - 56th IEEE Conference on Decision and Control, Dec 2017, Melbourne, Australia. pp.1-6. 〈hal-01651329〉

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