Please wait a minute...
Front. Inform. Technol. Electron. Eng.  2014, Vol. 15 Issue (7): 514-524    DOI: 10.1631/jzus.C1300342
    
复杂海洋生态系统的过程式生成与实时绘制
Rong Li, Xin Ding, Jun-hao Yu, Tian-yi Gao, Wen-ting Zheng, Rui Wang, Hu-jun Bao
State Key Lab of CAD & CG, Zhejiang University, Hangzhou 310027, China; PLA Unit 61741, China
Procedural generation and real-time rendering of a marine ecosystem
Rong Li, Xin Ding, Jun-hao Yu, Tian-yi Gao, Wen-ting Zheng, Rui Wang, Hu-jun Bao
State Key Lab of CAD & CG, Zhejiang University, Hangzhou 310027, China; PLA Unit 61741, China
 全文: PDF 
摘要: 研究目的:面向具有生物多样性的大范围复杂海洋生态环境,实现对其复杂几何的高效建模生成,同时实现实时绘制。
创新要点:我们使用了一种CPU和GPU混合的过程式生成流水线,从而充分发挥了CPU的灵活性和GPU的高计算性能,取得了整体上的高效率。
研究方法:首先,考虑了海底地形、波能、光能、生物属性等影响因素,提出了一种以竞争机制为原则的生态环境模拟过程,输出区域海底环境的生物空间分布(图4)。然后,针对海洋生物个体,提出了一个两阶段的过程式生成流水线(图2)。第一阶段,在CPU上通过解码一系列语法,生成粗糙的几何外形和高度紧凑的细节信息;第二阶段,基于现代GPU的强大硬件细分能力,实时解码细节信息,完成多细节层次的生物细节几何生成。最后,针对海洋生物之间的互动,系统定制了动态模拟模块。通过对复杂物理模型的简化,在CPU上实现对海洋生物整体形状形变的实时计算。在GPU上利用该形变计算结果,生成生物的形变细节(图11)。
重要结论:针对大范围海下生态环境,提出了一种高效的过程式建模和绘制系统,达到了复杂几何的高效生成及实时三维场景漫游效果。
关键词: 过程式生成海洋生态环境生物特性GPU加速    
Abstract: Underwater scene is one of the most marvelous environments in the world. In this study, we present an efficient procedural modeling and rendering system to generate marine ecosystems for swim-through graphic applications. To produce realistic and natural underwater scenes, several techniques and algorithms have been presented and introduced. First, to distribute sealife naturally on a seabed, we employ an ecosystem simulation that considers the influence of the underwater environment. Second, we propose a two-level procedural modeling system to generate sealife with unique biological features. At the base level, a series of grammars are designed to roughly represent underwater sealife on a central processing unit (CPU). Then at the fine level, additional details of the sealife are created and rendered using graphic processing units (GPUs). Such a hybrid CPU-GPU framework best adopts sequential and parallel computation in modeling a marine ecosystem, and achieves a high level of performance. Third, the proposed system integrates dynamic simulations in the proposed procedural modeling process to support dynamic interactions between sealife and the underwater environment, where interactions and physical factors of the environment are formulated into parameters and control the geometric generation at the fine level. Results demonstrate that this system is capable of generating and rendering scenes with massive corals and sealife in real time.
Key words: Procedural generation    Marine ecosystem    Biological feature    Graphic processing unit acceleration
收稿日期: 2013-12-01 出版日期: 2014-07-10
CLC:  TP391  
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  
Rong Li
Xin Ding
Jun-hao Yu
Tian-yi Gao
Wen-ting Zheng
Rui Wang
Hu-jun Bao

引用本文:

Rong Li, Xin Ding, Jun-hao Yu, Tian-yi Gao, Wen-ting Zheng, Rui Wang, Hu-jun Bao. Procedural generation and real-time rendering of a marine ecosystem. Front. Inform. Technol. Electron. Eng., 2014, 15(7): 514-524.

链接本文:

http://www.zjujournals.com/xueshu/fitee/CN/10.1631/jzus.C1300342        http://www.zjujournals.com/xueshu/fitee/CN/Y2014/V15/I7/514

[1] Gopi Ram , Durbadal Mandal , Sakti Prasad Ghoshal , Rajib Kar . 使用猫群算法优化线性天线阵列的最佳阵因子辐射方向图:电磁仿真验证[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 570-577.
[2] Lin-bo Qiao, Bo-feng Zhang, Jin-shu Su, Xi-cheng Lu. 结构化稀疏学习综述[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 445-463.
[3] Yuan-ping Nie, Yi Han, Jiu-ming Huang, Bo Jiao, Ai-ping Li. 基于注意机制编码解码模型的答案选择方法[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 535-544.
[4] Rong-Feng Zhang , Ting Deng , Gui-Hong Wang , Jing-Lun Shi , Quan-Sheng Guan . 基于可靠特征点分配算法的鲁棒性跟踪框架[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(4): 545-558.
[5] Wen-yan Xiao, Ming-wen Wang, Zhen Weng, Li-lin Zhang, Jia-li Zuo. 基于语料库的小学英语认识率及教材选词策略研究[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 362-372.
[6] . 一种基于描述逻辑的体系质量需求建模与验证方法[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 346-361.
[7] Ali Darvish Falehi, Ali Mosallanejad. 使用基于多目标粒子群算法多层自适应模糊推理系统晶闸管控制串联电容器补偿技术的互联多源电力系统动态稳定性增强器[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(3): 394-409.
[8] Jun-hong Zhang, Yu Liu. 应用完备集合固有时间尺度分解和混合差分进化和粒子群算法优化的最小二乘支持向量机对柴油机进行故障诊断[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 272-286.
[9] Li Weigang. 用于评估共同作者学术贡献的第一和其他合作者信用分配模式[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 180-194.
[10] Hui Chen, Bao-gang Wei, Yi-ming Li, Yong-huai Liu, Wen-hao Zhu. 一种易用的实体识别消歧系统评测框架[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(2): 195-205.
[11] Yue-ting Zhuang, Fei Wu, Chun Chen, Yun-he Pan. 挑战与希望:AI2.0时代从大数据到知识[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 3-14.
[12] Bo-hu Li, Hui-yang Qu, Ting-yu Lin, Bao-cun Hou, Xiang Zhai, Guo-qiang Shi, Jun-hua Zhou, Chao Ruan. 基于综合集成研讨厅的群体智能设计研究[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 149-152.
[13] Yong-hong Tian, Xi-lin Chen, Hong-kai Xiong, Hong-liang Li, Li-rong Dai, Jing Chen, Jun-liang Xing, Jing Chen, Xi-hong Wu, Wei-min Hu, Yu Hu, Tie-jun Huang, Wen Gao. AI2.0时代的类人与超人感知:研究综述与趋势展望[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 58-67.
[14] Yu-xin Peng, Wen-wu Zhu, Yao Zhao, Chang-sheng Xu, Qing-ming Huang, Han-qing Lu, Qing-hua Zheng, Tie-jun Huang, Wen Gao. 跨媒体分析与推理:研究进展与发展方向[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 44-57.
[15] Le-kui Zhou, Si-liang Tang, Jun Xiao, Fei Wu, Yue-ting Zhuang. 基于众包标签数据深度学习的命名实体消歧算法[J]. Frontiers of Information Technology & Electronic Engineering, 2017, 18(1): 97-106.