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In this paper we present an extension to the KinectFusion algorithm that allows a robust real-time face tracking and modeling using the Microsoft’s Kinect sensor. This is achieved changing two steps of the original algorithm: pre-processing and tracking. In the former, we use a real-time face detection algorithm to segment the face from the rest of the image. In the latter, we use a real-time head pose estimation to give a new initial guess to the Iterative Closest Point (ICP) algorithm when it fails and an algorithm to solve occlusion. Our approach is evaluated in a markerless augmented reality (MAR) system. We show that this approach can reconstruct faces and handle more face pose changes and variations than the original KinectFusion’s tracking algorithm. In addition, we show that the realism of the system is enhanced as we solve the occlusion problem efficiently at shader level.

KinectFusion for Faces: Real-Time 3D Face Tracking and Modeling Using a Kinect Camera for a Markerless AR System