Global Parameterization-based Texture Space Optimization
This addresses storage and GPU memory issues in rendering for graphics applications, but appears incremental as it builds on global parameterization methods.
The paper tackles the problem of inefficient texture mapping in computer graphics by optimizing texture space to be more compact, resulting in improved storage and rendering efficiency with computational robustness.
Texture mapping is a common technology in the area of computer graphics, it maps the 3D surface space onto the 2D texture space. However, the loose texture space will reduce the efficiency of data storage and GPU memory addressing in the rendering process. Many of the existing methods focus on repacking given textures, but they still suffer from high computational cost and hardly produce a wholly tight texture space. In this paper, we propose a method to optimize the texture space and produce a new texture mapping which is compact based on global parameterization. The proposed method is computationally robust and efficient. Experiments show the effectiveness of the proposed method and the potency in improving the storage and rendering efficiency.