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Item Transferring and Animating a non T-pose Model to a T-pose Model(The Eurographics Association, 2016) Hajari, Nasim; Cheng, Irene; Basu, Anup; Luis Gonzaga Magalhaes and Rafal MantiukNon T-pose animation is a technique that attempts to generate natural transformations between any non T-pose skeletons to the neutral T-pose skeleton. It is not always easy to extract or embed a T-pose animation skeleton into a 3D human model in an arbitrary initial position. This is even more problematic for natural human models obtained by 3D scanning, especially models of babies and kids. In addition, transforming a non T-pose to a T-pose requires a large amount of calculations. Hence, many commercially available software do not provide efficient methods to standardize non T-pose skeletons. This paper focuses on developing a simplified transformation method, which enables skeletons in arbitrary poses to be standardized and used in other media conveniently.Item Robust Transmission of Motion Capture Data using Interleaved LDPC and Inverse Kinematics(The Eurographics Association, 2016) Furtado, Antonio Carlos; Cheng, Irene; Dufaux, Frederic; Basu, Anup; T. Bashford-Rogers and L. P. SantosRecent advances in smart-sensor technology have improved precision in Motion Capture (MoCap) data for realistic animation. However, precision also imposes challenges on bandwidth. While research efforts have focussed on MoCap compression in recent years, little attention has been given to lossy transmission taking advantage of the human perceptual threshold, which allows many online applications, e.g., interactive games, on-demand broadcast, movies and tutoring using dynamic motion sequences. Given the growing applications on mobile devices and wireless networks, associated with insufficient bandwidth, unreliable connection and potential interference or shadowing, data loss is inevitable. We introduce a new Representation for MoCap data, integrating Interleaved Low-Density Parity-Check (I-LDPC), with Keyframe-based Interpolation and Inverse Kinematics, to better address the problem of MoCap data loss during transmission. We believe this is the first study to address robust transmission of MoCap data considering loss. Experimental results assessed using mean opinion scores demonstrate that our approach achieves substantial improvement over alternative transmission methods.