Registration and integration of multiple depth images using signed distance function

Depth camera is a new technology that has potential to radically change the way humans record the world and interact with 3D virtual environments. With depth camera, one can have access to depth information up to 30 frames per second, which is much faster than previous 3D scanners. This speed enables new applications, in that objects are no longer required to be static for 3D sensing. There is, however, a trade-off between the speed and the quality of the results. Depth images acquired with current depth cameras are noisy and have low resolution, which poses a real obstacle to incorporating the new 3D information into computer vision techniques. To overcome these limitation, the speed of depth camera could be leveraged to combine data from multiple depth frames together. Thus, we need a good registration and integration method that is specifically designed for such low quality data. To achieve that goal, in this paper we propose a new method to register and integrate multiple depth frames over time onto a global model represented by an implicit moving least square surface.