Multimodal Visual Features Based Natural Human-Computer Interaction
Guan Ye-pen · Dianzi xuebao · 2013
A novel human-computer interaction(HCI)is developed based on multimodal visual features aiming atsome limits at present.Two-dimensional Gabor wavelet is adopted to extract some visual features of global face orientation,which overcomes some difficulties including extraction of some facial distinct features,discrimination among some different facial orientations.An efficient and fast approach to locating center of eyes is proposed based on facial geometric distributions without considering facial resolution,eyes closing or opening and user′s wearing.Some prominent multimodal visual features for classification are selected to machine learning and training to determine the pointing target after evaluating performance of some extracted visual features.Nonwearable and natural HCI modal can be realized in which user can move freely without wearing any markers when he points atsome targets.Their daily skills can be exerted fully during HCI.Experiment results indicate that the developed approach is efficient and can be used to natural non-wearable HCI.