Rendering Optimization Algorithm for Large-Scale Scene Based on Virtual Reality
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    Abstract:

    At present, the demand for large-scale scene model generation is increasing. A region-based automatic Levels Of Details (LOD) construction algorithm is proposed. The algorithm is based on the dynamic mesh simplification algorithm. In the process of game design and production, game developers often need to work on the art. The model provided by the department staff is optimized in order to simplify the number of faces of the model and not change the appearance of the model. Today’s popular LOD technology is very good at handling this situation, judging the distance between the model and the camera. After a certain range is exceeded, the models of different levels are automatically retrieved. When the model is far away from the camera, the model with a low number of faces is replaced by the high-modulus. This can increase the frame rate and reduce the number of triangles and the number of vertices in front of the camera to reduce rendering stress. The simplification of the general model is divided into the simplification of static and dynamic models. In most cases, the programmer will let the art department provide several sets of different face models or reduce the face of the high model and save it into multiple mesh through the model simplification tool. When the program is running, according to the distance between the model and the camera, the mesh is replaced dynamically. This is a static method. Here we will try to use a combination of dynamic mesh simplification and LOD technology. This new algorithm greatly simplifies the operation process, while the artist only needs to provide a model, then the programmer can use this method to generate low-modules of different magnitudes, and automatically pick up models of different precision according to the distance between the camera and the model.

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叶诚,罗训.基于虚拟现实的复杂场景加载优化算法.计算机系统应用,2020,29(6):235-240

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History
  • Received:October 17,2019
  • Revised:November 15,2019
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  • Online: June 12,2020
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