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自然现象的数据获取与模拟 被引量:3

Data acquisition and simulation of natural phenomena
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摘要 数学物理建模和图形学仿真得到的各种虚拟自然现象,可以在一定程度上满足用户的感知体验,但却难以与真实自然现象具有高精度物理一致性.自然现象的数据获取与模拟技术从真实自然现象中直接获取多维多模态数据,根据实获数据从外观、物理、行为等多方面建立与真实自然现象高度一致的数字化模型,使得虚拟自然现象成为真实自然现象的直接映射.这种研究方法有利于虚拟现实可信度与可用性问题的解决.目前,自然现象的数据获取与模拟技术研究尚处于起步阶段,本文对其进行了综述.首先概述了模拟自然现象的基本方法和技术,然后根据自然现象基本元素的不同,分别对光照、水、火焰、烟雾、动态地形等自然现象的数据获取与模拟方法的研究现状进行了论述;最后针对自然现象数据获取与模拟研究中存在的问题和未来可能的发展方向,指出了需要进一步研究解决的若干理论和技术问题. Virtual natural phenomena obtained through mathematical-physical modeling and simulation as well as graphics emulation can meet the user’s requirements for sensory experiences to a certain extent but they can hardly have the same accurate physical consistency as real natural phenomena.The technology for data acquisition and natural phenomena simulation can enable us to obtain multi-dimensional and multi-modal data directly from real natural phenomena and,based on these real data,to establish digital models highly consistent with real natural phenomena in appearance,physics,behavior or many other aspects,thus making a virtual natural phenomenon a direct mapping of real natural phenomenon.This approach is conducive to resolving problems concerning the reliability and availability of virtual reality.At present the technology for acquiring and simulating dada of natural phenomena is still in its initial stage.This paper gives a review of the related investigations. Firstly,we briefly introduce the basic methods and techniques concerned,then,based on the diffierence between the basic elements of various natural phenomena,we discuss the current studies on such natural phenomena as light,water,fire,smoke,dynamic terrain,etc.,and finally,in connection with issues in the present research and possible future direction of development,we put forth a number of theoretical and technical problems,hoping they can be resolved in the near future.
作者 赵沁平
出处 《中国科学:信息科学》 CSCD 2011年第4期385-419,共35页 Scientia Sinica(Informationis)
基金 国家基础研究发展计划(批准号:2009CB320805)
关键词 自然现象 数据获取 模拟 数据驱动 可信度 natural phenomena data acquisition simulation data driven reliability
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