Compact and Accurate 3-D Face Modeling Using an RGB-D Camera: Let's Open the Door to 3-D Video Conference

Abstract

We present a method for producing an accurate and compact 3-D face model in real time using a low cost RGB-D sensor like the Kinect camera. We extend and use Bump Images for highly accurate and low memory consumption 3-D reconstruction of the human face. Bump Images are generated by representing the Cartesian coordinates of points on the face in the spherical coordinate system whose origin is the center of the head. After initialization, the Bump Images are updated in real time with every RGB-D frame with respect to the current viewing direction and head pose that are estimated using the frame-to-global-model registration strategy. While high accuracy of the representation allows to recover fine details, low memory use opens new possible applications of consumer depth cameras such as 3-D video conferencing. We validate our approach by quantitatively comparing our result with the result obtained by a commercial high resolution laser scanner. We also discuss the potential of our proposed method for a 3-D video conferencing application with existing internet speeds.