Digitization of people and objects for virtual museum applications

We present a system for the digitization of real people and objects for the integration into computer-generated virtual scenes. We target the creation of natural and realistic representations of historical sites, artifacts and objects, which can be integrated into virtual museum applications. Using Virtual Reality (VR) glasses, a user can stroll through a virtual exhibition and get an immersive impression of the artifacts. Our system allows to capture and digitize static as well as moving people and objects. In this way additionally a historical context can be generated in the virtual scene which fits to the artifacts and objects. Actors can be inserted to reconstructed historical sites to create a realistic and convincing historical experience. Virtual guides could provide additional information about the exhibits and enrich the scene. From a technical point, our system combines computer graphics and image-based rendering tools to represent real persons through realistic and natural moving 3D models. In addition, methods for the passive digitization of highly detailed 3D models have been developed.

[1]  Michael M. Kazhdan,et al.  Screened poisson surface reconstruction , 2013, TOGS.

[2]  Peter Eisert Model-Based Camera Calibration Using Analysis by Synthesis Techniques , 2002, VMV.

[3]  Sebastian Nowozin,et al.  Structured Prediction and Learning in Computer Vision , 2011 .

[4]  Peter Eisert,et al.  High-resolution depth for binocular image-based modeling , 2014, Comput. Graph..

[5]  Peter Eisert,et al.  Real-time 3D body reconstruction for immersive TV , 2016, 2016 IEEE International Conference on Image Processing (ICIP).

[6]  Oliver Schreer,et al.  Visibility-driven patch group generation , 2014, 2014 International Conference on 3D Imaging (IC3D).

[7]  Peter Eisert,et al.  An Iterative Method for Improving Feature Matches , 2013, 2013 International Conference on 3D Vision.

[8]  Oliver Schreer,et al.  Real-time patch sweeping for high-quality depth estimation in 3D video conferencing applications , 2011, Electronic Imaging.

[9]  David G. Lowe,et al.  Object recognition from local scale-invariant features , 1999, Proceedings of the Seventh IEEE International Conference on Computer Vision.

[10]  Paolo Cignoni,et al.  VCLab's Tools for 3D range data processing , 2003, VAST.

[11]  Roberto Manduchi,et al.  Bilateral filtering for gray and color images , 1998, Sixth International Conference on Computer Vision (IEEE Cat. No.98CH36271).