Abstract

With the wide-spread of consumer 3D-TV technology, stereoscopic videoconferencing systems are emerging. However, the special glasses participants wear to see 3D can create distracting images. This paper presents a computational framework to reduce undesirable artifacts in the eye regions caused by these 3D glasses. More specififically, we add polarized fifilters to the stereo camera so that partial images of reflflection can be captured. A novel Bayesian model is then developed to describe the imaging process of the eye regions including darkening and reflflection, and infer the eye regions based on Classifification ExpectationMaximization (EM). The recovered eye regions under the glasses are brighter and with little reflflections, leading to a more nature videoconferencing experience. Qualitative evaluations and user studies are conducted to demonstrate the substantial improvement our approach can achieve