804483
Consistent parametrization by quinary subdivision for remeshing and mesh metamorphosis
The vertex correspondence establishment among multiple objects is a versatile operation in computer graphics and geometry processing. We propose a systematic method called recursive quinary subdivision to efficiently find a dissection for a meshed object of genus-zero with little user input. The process can be easily extended to multiple objects, taking into account the alignment of extra feature points for applications such as mesh metamorphosis, to derive a common dissection. Based on the dissection and the parameterization associated with each resulting patch, uniform or adaptive remeshing can be performed to yield a set of semi-regular meshes. Moveover, geometric details can be easily resampled and stored as normal maps. We demonstrate the mesh metamorphosis application between two or more objects based on the vertex correspondence established by the common dissection and parameterization.
14278581
Texture Adaptation for Progressive Meshes
Level-of-detail modeling is a vital representation for real-time applications. To support texture mapping progressive meshes (PM), we usually allow the whole PM sequence to share a common texture map. Although such a common texture map can be derived by using appropriate mesh parameterizations that consider the minimization of geometry stretch, texture stretch, or even the texture deviation introduced by edge collapses, we have found that even with a well parameterized texture map, the texture mapped PM still reveals apparent texture distortion due to geometry changes and the nature of linear interpolation used by texture mapping hardware. In this paper, we propose a novel, simple, and efficient approach that adapts texture content for each edge collapse, aiming to eliminate texture distortion. A texture adaptation and its inverse are local and incremental operations that can be fully supported by texture mapping hardware, the render-to-texture feature, and the fragment shader. Once the necessary correspondence in the partition of texture space is built during the course of PM construction, the texture adaptation or its inverse can be applied on the fly before rendering the simplified or refined model with texture map. We also propose the mechanism of indexing mapping to reduce blurred artifacts due to under-sampling that might be introduced by texture adaptation. 
 
 
 
Keywords: texture mapping progressive meshes, mesh simplification, mesh parameterization, texture distortion Categories and Subject Descriptors (according to ACM CCS): I.3.7 [Computer Graphics]: Three-Dimensional Graphics and Realism Color, shading, shadowing, and texture
10757708
Rendering complex scenes using spatial subdivision and textured LOD meshes
Abstract We present a hybrid rendering scheme that explores the locality of visibility at the cost of extra storage and prefetching, and makes a tradeoff between image quality and rendering efficiency by using textured level-of-detail (LOD) meshes. The space is first subdivided into cells. For each cell, inside objects are rendered as normal while outside objects are rendered as textured LOD meshes using projective texture mapping. The textured LOD meshes are object based and derived from the original meshes based on the captured depth images viewed at the centers of the cell and its adjacent cells. With such a textured LOD mesh, problems commonly found in image-based rendering, such as the hole problem due to occlusion among objects and the gap problems due to resolution mismatch, can be avoided. The size of holes due to self-occlusion is constrained to be within a user-specified tolerance. Several scenes with millions of polygons have been tested and higher than 200 FPS has been achieved with a little loss of image quality.
32443419
Evolution modeling of complex network base on spatial structure
Evolution modeling of complex network is a fruitful field, yet few studies have modeled system with spatial information like human brain, and methods for modeling spatial system tend to get inconsistent results. The current study intends to improve it by modeling 3-dimension complex evolution model. With the assumption that probability of having edge depended on distance between nodes, we got a network follows power law.