Improve Computer Visualization of Architecture Based on the Bayesian Network

• 作者: Chan Gao Tao Shen Yukari Nagai
• 来源期刊: 计算机、材料和连续体(英文)
• 学科: 工学
• 关键词: 3Ds MAX ARCHITECTURAL VISUALIZATION application GEOMETRIC RECONSTRUCTION Bayes.
• 年，卷（期）: 2019,（2）
• 页码范围: 307-318
• 页数: 12页
• 分类号: TP3

摘要

Computer visualization has marvelous effects when it is applied in various fields,especially in architectural design.As an emerging force in the innovation industry,architects and design agencies have already demonstrated the value of architectural visual products in actual application projects.Based on the digital image technology,virtual presentation of future scenes simulates architecture design,architectural renderings and multimedia videos.Therefore,it can help design agencies transform the theoretical design concept into a lively and realistic visual which can provide the audience with a clearer understanding of the engineering and construction projects.However,it is challenging for designers to produce satisfactory renderings due to the frequent fault data during rendering.In this paper,we use the 3Ds MAX as the operating platform and we present an algorithm based on the Bayesian network to construct a vector representation of the fault data.On this basis,a case study of 3D Max’application has also been presented.