Journals
  Publication Years
  Keywords
Search within results Open Search
Please wait a minute...
For Selected: Toggle Thumbnails
Improved small feature culling for large scale process plant model based on octree
DU Zhenlin, TANG Weiqing, QIN Li, LI Shicai
Journal of Computer Applications    2017, 37 (9): 2626-2630.   DOI: 10.11772/j.issn.1001-9081.2017.09.2626
Abstract779)      PDF (825KB)(490)       Save
To eliminate the drawbacks of traditional small feature culling algorithm which processing granularity are triangles and can't efficiently cope with the number of vertexes and triangles up to hundreds of millions in a certain time period, an improved small feature culling algorithm for large scale process plant based on octree was proposed. Based on the component primitive characteristics and spatial characteristics of the process plant model, the value of screen for quantizing the size of component was proposed, and the established octree and the value of screen were combined to estimate the upper limit of the number of pixels, so as to quickly determine whether the component would be culled or not. The experimental results show that the proposed algorithm is simple and effective. Compared with the current popular review software after loading the factory model with 10000 pipelines, the frame rate is increased by at least 50%, which greatly improves the platform's fluency. Process factory industry and graphics platform as a whole to enhance the level of design has a positive meaning.
Reference | Related Articles | Metrics