Capture of arm-muscle deformations using a depth-camera

• Authors: Nadia Robertini;Thomas Neumann;Kiran Varanasi;Christian Theobalt
• Venue: Proceedings of the 10th European Conference on Visual Media Production
• Year: 2013

Modeling realistic skin deformations due to underneath muscle bulging has a wide range of applications in medicine, entertainment and art. Current acquisition systems based on dense markers and multiple synchronized cameras are able to record and reproduce fine-scale skin deformations with sufficient quality. However, the complexity and the high cost of these systems severely limit their applicability. In this paper, we propose a method for reconstructing fine-scale arm muscle deformations using the Kinect depth camera. The captured data from the depth camera has no temporal contiguity and suffers from noise and sensory artifacts, and thus unsuitable by itself for potential applications in visual media production or biomechanics. We process noisy depth input to obtain spatio-temporally consistent 3D mesh reconstructions showing fine-scale muscle bulges over time. Our main contribution is the incorporation of statistical deformation priors into the spatiotemporal mesh registration progress. We obtain these priors from a previous dataset of a limited number of physiologically different actors captured using a high fidelity acquisition setup, and these priors help provide a better initialization for the ultimate non-rigid surface refinement that models deformations beyond the range of the previous dataset. Thus, our method is an easily scalable framework for bootstrapping the statistical muscle deformation model, by extending the set of subjects through a Kinect based acquisition process. We validate our spatio-temporal surface registration method on several arm movements performed by people of different body shapes.