3D Archive System for Traditional Performing Arts

Abstract

We developed a 3D archive system for Japanese traditional performing arts. The system generates sequences of 3D actor models of the performances from multi-view video by using a graph-cuts algorithm and stores them with CG background models and related information. The system can show a scene from any viewpoint as follows; the 3D actor model is integrated with the background model and the integrated model is projected to a viewpoint that the user indicates with a viewpoint controller. A challenge of generating the actor models is how to reconstruct thin or slender parts. Japanese traditional costumes for performances include slender parts such as long sleeves, fans and strings that may be manipulated during the performance. The graph-cuts algorithm is a powerful 3D reconstruction tool but it tends to cut off those parts because it uses an energy-minimization process. Hence, the search for a way to reconstruct such parts is important for us to preserve these arts for future generations. We therefore devised an adaptive erosion method that works on the visual hull and applied it to the graph-cuts algorithm to extract interior nodes in the thin parts and to prevent the thin parts from being cut off. Another tendency of the reconstruction method using the graph-cuts algorithm is over-shrinkage of the reconstructed models. This arises because the energy can also be reduced by cutting inside the true surface. To avoid this tendency, we applied a silhouette-rim constraint defined by the number of the silhouette-rims passing through each node. By applying the adaptive erosion process and the silhouette-rim constraint, we succeeded in constructing a virtual performance with costumes including thin parts. This paper presents the results of the 3D reconstruction using the proposed method and some outputs of the 3D archive system.

DOI: 10.1007/s11263-011-0434-2

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Cite this paper

@article{Hisatomi20113DAS, title={3D Archive System for Traditional Performing Arts}, author={Kensuke Hisatomi and Miwa Katayama and Kimihiro Tomiyama and Yuichi Iwadate}, journal={International Journal of Computer Vision}, year={2011}, volume={94}, pages={78-88} }