Efficient Simplification Methods for Generating High Quality LODs of 3D Meshes

Abstract

Two simplification algorithms are proposed for automatic decimation of polygonal models, and for generating their LODs. Each algorithm orders vertices according to their priority values and then removes them iteratively. For setting the priority value of each vertex, exploiting normal field of its one-ring neighborhood, we introduce a new measure of geometric fidelity that reflects well the local geometric features of the vertex. After a vertex is selected, using other measures of geometric distortion that are based on normal field deviation and distance measure, it is decided which of the edges incident on the vertex is to be collapsed for removing it. The collapsed edge is substituted with a new vertex whose position is found by minimizing the local quadric error measure. A comparison with the state-of-the-art algorithms reveals that the proposed algorithms are simple to implement, are computationally more efficient, generate LODs with better quality, and preserve salient features even after drastic simplification. The methods are useful for applications such as 3D computer games, virtual reality, where focus is on fast running time, reduced memory overhead, and high quality LODs.

Feature Preserving Mesh Simplification Using Feature Sensitive Metric

“…This is an limitation of FS method that there exists a tradeoff between appearance, speed and interactivity, but it is still faster than some other appearance preserving based method like [15], that is mentioned as three to twenty times slower than QEM. For fair comparison, we do not introduce any special scheme for acceleration, so there are quite a lot strategies which can be employed for further improvement, e.g., using vertex heap rather than edge heap [18] . The performance of FS method is also related to the input quality, for the reason that a complex model may bring more iteration steps.…”

Optimization Techniques for 3D Graphics Deployment on Mobile Devices

“…As earlier mentioned, the capabilities of mobile hardware for 3D graphics re-production grow On-device optimization [8] x [33] x x [34] x [35] x [36] x [37] x [38] x x [39] x [40] x x [41] x [42] x [43] x x [44] x [53] x [54] x x [55] x x [56] x x [57] x x [58] x [60] x [61] x [62] x x [63] x x [64] x x [65] x [66] x [67] x [68] x [69] x [70] x [71] x [72] x [73] x [74] x x [76] x x [77] x [78] x [79] x [80] x [81] x [82] x [83] x [84] x extremely fast. For instance, 3D rendering performance of Tegra4 is roughly three-four times higher when compared to the previous generation [45].…”

“…Secondly, the simplification methods should provide a compact presentation of 3D graphics to lower the requirements for the wireless bandwidth and the local storage on the mobile device [56]. Thirdly, the simplification methods should preserve the vertex attributes such as per-vertex normals, texture coordinates and color information to retain adequate visual quality of the 3D graphics [58]. Finally, it is important to emphasize that this article focuses only on the simplification methods that are potentially suitable for deploying 3D graphics on mobile devices.…”

Simplification of 3D Triangular Mesh for Level of Detail Computation

“…FSIMP algorithm is two times faster than QSlim method. In 2009, he improved FSIMP algorithm [8] to reflect the local geometric features of each vertex. It measured the geometric distortion based on normal field deviation and distance to select a vertex.…”