View-Independent Enhanced 3D Reconstruction of Non-rigidly Deforming Objects

In this paper, we target enhanced 3D reconstruction of non-rigidly deforming objects based on a view-independent surface representation with an automated recursive filtering scheme. This work improves upon the KinectDeform algorithm which we recently proposed. KinectDeform uses an implicit viewdependent volumetric truncated signed distance function (TSDF) based surface representation. The view-dependence makes its pipeline complex by requiring surface prediction and extraction steps based on camera’s field of view. This paper proposes to use an explicit projection-based Moving Least Squares (MLS) surface representation from point-sets. Moreover, the empirical weighted filtering scheme in KinectDeform is replaced by an automated fusion scheme based on a Kalman filter. We analyze the performance of the proposed algorithm both qualitatively and quantitatively and show that it is able to produce enhanced and feature preserving 3D reconstructions.