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View Frustum Culling Algorithm for Scene Based on Adaptive Binary Tree

机译:基于自适应二叉树的视景视锥剔除算法

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Enhance the realism of scene rendering and improve the rendering speed of the three-dimensional scene is the main task in the field of visualization. As a key part before the scene is drawn, the organization and visibility judgment of the scene are paid more and more attention, the performance of scene organization and visibility judgment affects the quality of subsequent scene rendering. In order to make up for the shortcomings of the traditional scene organization in practical application, In this paper, adaptive binary tree (ABT) scene organization algorithm is responsible for the scene to be reasonably divided. Based on the structure of the scene, the culling algorithm based on the bounding sphere and the bounding box is responsible for culling the nodes in the scene tree, Objects that are manipulated during culling are the bounding sphere and bounding boxes in the node. Experiments show that the hierarchical view frustum culling algorithm based on the bounding sphere and the bounding box greatly reduces the number of nodes involved in culling, improves the culling accuracy, has better culling efficiency and higher stability, further improve the performance of subsequent scene rendering.
机译:增强场景渲染的真实性并提高三维场景的渲染速度是可视化领域的主要任务。作为场景绘制之前的关键部分,场景的组织和可见性判断越来越受到关注,场景组织和可见性判断的性能会影响后续场景渲染的质量。为了弥补传统场景组织在实际应用中的不足,本文采用自适应二叉树(ABT)场景组织算法对场景进行合理划分。基于场景的结构,基于边界球和边界框的剔除算法负责对场景树中的节点进行剔除,剔除过程中要处理的对象是节点中的边界球和边界框。实验表明,基于边界球和边界框的层次视图视锥截取算法大大减少了剔除涉及的节点数量,提高了剔除精度,具有更好的剔除效率和更高的稳定性,进一步提高了后续场景渲染的性能。

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