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 view-dependent 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.