  Research into object deformations using computer vision techniques has been
under intense study in recent years. A widely used technique is 3D non-rigid
registration to estimate the transformation between two instances of a
deforming structure. Despite many previous developments on this topic, it
remains a challenging problem. In this paper we propose a novel approach to
non-rigid registration combining two data spaces in order to robustly calculate
the correspondences and transformation between two data sets. In particular, we
use point color as well as 3D location as these are the common outputs of RGB-D
cameras. We have propose the Color Coherent Point Drift (CCPD) algorithm (an
extension of the CPD method [1]). Evaluation is performed using synthetic and
real data. The synthetic data includes easy shapes that allow evaluation of the
effect of noise, outliers and missing data. Moreover, an evaluation of
realistic figures obtained using Blensor is carried out. Real data acquired
using a general purpose Primesense Carmine sensor is used to validate the CCPD
for real shapes. For all tests, the proposed method is compared to the original
CPD showing better results in registration accuracy in most cases.
