VirtualizeMe introduces a new design for a fully immersive Tele-Immersion system for remote collaboration and virtual world interaction. This system introduces a new avatar creation approach full-filling four main attributes: high resolution, scalability, flexibility and affordability. This is achieved by a total separation of reconstruction and rendering and exploiting the capabilities of modern graphic cards. The high resolution is achieved by using as much of the input information as possible through lossless compression of the input data and introducing a focused volumetric visual hull reconstruction. The resulting avatar allows eye-to-eye collaboration for remote users. The interaction with the virtual world is facilitated by the volumetric avatar model and allows a fully immersive system. This paper shows a proof of concept based on publicly available pre-recorded data to allow easier comparison.

This paper introduces a region-of-interest visual hull refinement technique, based on flexible voxel grids for volumetric visual hull reconstructions. Region-of-interest refinement is based on a multi-pass process, beginning with a focussed visual hull reconstruction, resulting in a first 3D approximation of the target, followed by a region-of-interest estimation, tasked with identifying features of interest, which in turn are used to locally refine the voxel grid and extract a higher-resolution surface representation for those regions. This approach is illustrated for the reconstruction of avatars for use in tele-immersion environments, where head and hand regions are of higher interest. To allow reproducability and direct comparison a publicly available data set for human visual hull reconstruction is used. This paper shows that region-of-interest reconstruction of the target is faster and visually comparable to higher resolution focused visual nhull reconstructions. This approach reduces the amount of data generated through the reconstruction, allowing faster post processing, as rendering or networking of the surface voxels. Reconstruction speeds support smooth interactions between the avatar and the virtual environment, while the improved resolution of its facial region and hands creates a higher-degree of immersion and potentially impacts the perception of body language, facial expressions and eye-to-eye contact.

Tele-Immersion depends on face-to-face, viewpoint corrected, stereoscopic, virtual environments, allowing users to naturally interact with each other and the digital environment surrounding them, via realistic avatars. This paper presents an extraction, modeling and communication methodology for the creation of the needed avatars, based on a scalable focused disparity map (FDM) approach. The FDM enables variable distance reconstruction of dynamic target objects despite restrictions in disparity range. Combined with a pixel-based disparity cost interpolation, a sub-pixel disparity refinement is achieved, providing a high depth-resolution and smooth reconstruction of the target objects. This technique approaches real-time characteristics, extracting avatar models and communicating them to remote render nodes at 15 frames per second.