景观表现中高真实度竹林仿真的研究  被引量:4

Study on high-fidelity bamboo forest simulation in landscape performance

在线阅读下载全文

作  者:何秋海 彭月橙[1] 黄心渊[1,2] 

机构地区:[1]北京林业大学艺术设计学院,北京100083 [2]中国传媒大学动画与数字艺术学院,北京100024

出  处:《计算机工程与应用》2015年第3期175-180,共6页Computer Engineering and Applications

基  金:中央高校基本科研业务费专项资金资助(No.RW2011-29)

摘  要:高真实度大场景植物仿真技术一直是景观表现中虚拟植物仿真建模和渲染研究的热点和难点。提出了一套从贴图数据采集,植物仿真建模到高仿真森林景观表现的完整解决方案。该方案从竹林形态特征结构、贴图数据采集、自然生长环境三个方面实现竹林的高仿真表现。通过竹叶形态、竹叶分布、模型面数、多角度还原度等因素的不断对比和改进,形成三套凤尾竹建模方案。根据渲染时间和内存使用的数据对比,得到了资源最优化真实度最大化的建模方法,解决了大规模虚拟森林模型运算的速度问题;根据云南当地凤尾竹林的实际景观,利用多层次混合光照模拟技术搭建完整的竹林场景,解决了现实环境中复杂的光照模拟问题。最终实现了在提高渲染速度的前提下依然保证高仿真的竹林景观表现效果的目标。The research of high-fidelity simulation technology in plant modeling and rendering of virtual large scale forest landscape is a hot and difficult point in landscape performance. This paper proposes a complete solution, which contains collecting texture data, plant simulation modeling and high-fidelity forest simulation of landscape performance. This solution focuses on three aspects of high-fidelity simulation, they are bamboo morphological structure, texture data collection and the natural habitat. With continuously comparing and improving the key elements of bamboo modelling, such as the shape and distribution of bamboo leaves, the faces of model, and the simulation of different perspectives, it proposes three plans of bamboo modelling. According to the comparison of the time of rendering and the usage of memory, it gets the balance method of maximum efficiency and high-fidelity, which solves the computing speed of virtual large scale landscape. According to the real bamboo landscape in Yunnan Province, it uses the multi-layer hybrid illumination simulation technology to build a complete bamboo landscape. This research approaches the target of ensuring high-fidelity forest landscape simulation with improving rendering speed.

关 键 词:植物仿真 景观表现 三维建模 光照模拟 

分 类 号:TP39[自动化与计算机技术—计算机应用技术]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象