Informatica

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.

The study of 3‐D indoor accurate scenery modeling is an active research area. The produced model can be used in a number of virtual reality applications, in digital documentation of monuments and sites, and so on. Digital photogrammetry and CAD technology have to play a vital role in this field. Photogrammetry's contribution is mainly on data acquisition from imagery, whilst the necessary image knowledge is derived from geometry and topology of image contents. While the first is traditionally used, the second one only lately is been tackled.