Predictor-Based Control of Human Response to a Dynamic 3D Face Using Virtual Reality

Article type: Research Article

Authors: Kaminskas, Vytautas | Ščiglinskas, Edgaras^{; *}

Affiliations: Faculty of Informatics, Vytautas Magnus University, Vileikos g. 8, LT-44404, Kaunas, Lithuania. E-mails: vytautas.kaminskas@vdu.lt, edgaras.sciglinskas@vdu.lt

Correspondence: [*] Corresponding authors.

Abstract: This paper introduces how predictor-based control principles are applied to the control of human excitement signal as a response to a 3D face virtual stimuli. A dynamic human 3D face is observed in a virtual reality. We use changing distance-between-eyes in a 3D face as a stimulus – control signal. Human responses to the stimuli are observed using EEG-based signal that characterizes excitement. A parameter identification method for predictive and stable model building with the smallest output prediction error is proposed. A predictor-based control law is synthesized by minimizing a generalized minimum variance control criterion in an admissible domain. An admissible domain is composed of control signal boundaries. Relatively high prediction and control quality of excitement signals is demonstrated by modelling results.

Keywords: dynamic virtual 3D face, human response, virtual reality, predictive input–output model, generalized minimum variance control

Journal: Informatica, vol. 29, no. 2, pp. 251-264, 2018