Eye gaze correction with stereovision for video-teleconferencing

The lack of eye contact in desktop video teleconferencing substantially reduces the effectiveness of video contents. While expensive and bulky hardware is available on the market to correct eye gaze, researchers have been trying to provide a practical software-based solution to bring video-teleconferencing one step closer to the mass market. This paper presents a novel approach: based on stereo analysis combined with rich domain knowledge (a personalized face model), we synthesize, using graphics hardware, a virtual video that maintains eye contact. A 3D stereo head tracker with a personalized face model is used to compute initial correspondences across two views. More correspondences are then added through template and feature matching. Finally, all the correspondence information is fused together for view synthesis using view morphing techniques. The combined methods greatly enhance the accuracy and robustness of the synthesized views. Our current system is able to generate an eye-gaze corrected video stream at five frames per second on a commodity 1 GHz PC.