Simplified gazecorrection method using 3D mesh warping Under the typical video communication configuration in which a camera is placed on top or at lateral side of a monitor, the facetoface video communication has an inherent difficulty of poor eye contacts since the users stare at the monitor screen rather than directly seeing the camera lens. In this paper, we propose an image warping technique for gazecorrection which performs 3D warping of face object in the given image by a certain correction angle. The correction angle which is the angle between the direction of eye gaze and that to the camera is estimated in an unsupervised way by using eye tracking technique. Experimental result with real image data shows much enhanced naturalness which the facetoface video communication has to offer.

Where Am I Looking: Localizing Gaze In Reconstructed 3D Space We propose a method to estimate the 3D gaze of the observer onto the scene using a portable eye tracker with a monocular camera. We reconstruct the 3D scene using Structure from Motion (SfM) and use camera pose and 3D reconstruction information of the scene to localize the position and pose of the observer in the 3D reconstructed space. Along with the position, we can obtain the 2D gaze of the observer using an eyetracker. Each person may have a different perspective of the same 3D object in the scene, observing it from different positions. We use this information to fuse these multiple perspectives in 3D space to get a better understanding of how differently each observer perceives the same scene, compared to others. In the entire system, we developed a convolutional neural network to detect and track eye movement and a camera relocalization method to localize the camera in 3D environment. Based on our novel eye tracking and camera relocalization methods, we can accurately localize the gaze in the 3D reconstructed environment.