Simultaneous super-resolution and 3D video using graph-cuts

This paper presents a new method to increase the quality of 3D video, a new media developed to represent 3D objects in motion. This representation is obtained from multi-view reconstruction techniques that require images recorded simultaneously by several video cameras. All cameras are calibrated and placed around a dedicated studio to fully surround the models. The limited quality and quantity of cameras may produce inaccurate 3D model reconstruction with low quality texture. To overcome this issue, first we propose super-resolution (SR) techniques for 3D video: SR on multi-view images and SR on single-view video frames. Second, we propose to combine both super-resolution and dynamic 3D shape reconstruction problems into a unique Markov Random Field (MRF) energy formulation. The MRF minimization is performed using graph-cuts. Thus, we jointly compute the optimal solution for super-resolved texture and 3D shape model reconstruction. Moreover, we propose a coarse-to-fine strategy to it...

• Type: Conference
• Year: 2008
• Where: CVPR
• Authors: Tony Tung, Shohei Nobuhara, Takashi Matsuyama
• Keywords: Challenging 3d Video, Computer Vision, CVPR 2008, Dynamic 3d Shape, Inaccurate 3d Model, Multi-view Reconstruction Techniques, Shape Model Reconstruction