Create Avatars using Kinect in Real-time

Real-time 3D reconstruction of the human body has many applications in anthropometry, telecommunications, gaming, fashion, and other areas of human-computer interaction. In this paper a novel framework is presented for reconstructing the 3D model of the human body from a sequence of RGB-D frames. The reconstruction is performed in real time while the human subject moves arbitrarily in front of the camera. The method employs a novel parameterization of cylindrical-type objects using Cartesian tensor and b-spline bases along the radial and longitudinal dimension respectively. The proposed model, dubbed tensor body, is fitted to the input data using a multi-step framework that involves segmentation of the different body regions, robust filtering of the data via a dynamic histogram, and energy-based optimization with positive-definite constraints. A Riemannian metric on the space of positive-definite tensor splines is analytically defined and employed in this framework. The efficacy of the presented methods is demonstrated in several real-data experiments using the Microsoft Kinect sensor. The full article can be found at the end of this PDF document. The citation of the published article is: A. Barmpoutis. Tensor Body: Real-time Reconstruction of the Human Body and Avatar Synthesis from RGB-D, IEEE Transactions on Cybernetics 43(5), Special issue on Computer Vision for RGB-D Sensors: Kinect and Its Applications, October 2013, pp. 1347-1356.