3D Model Optimization and Roaming of Large Data Volume Virtual Landscape
Abstract
Due to the huge data in a 3D model of a large-area virtual landscape, the optimization method of the modeling process is well worth studying. We examine it from three aspects: selecting modeling tools, reducing model redundancy and complexity, and reducing
model file size. The architecture of the virtual scene roaming system used in the modelling is given. The realization process of the roaming system is examined from three aspects: 3D model data transformation, roaming path and perspective design and finally, roaming system integration. A data compression and conversion algorithm is provided in this paper. Finally, a virtual campus roaming system with a large data volume is implemented on the Visual C++ software platform. The system has good real-time interaction and scalability.
The Internet age today means that data includes every input into a search engine, as well as every transaction on shopping websites. The term for the huge data sets that have resulted is called Big Data. Those data sets are so large they cannot be collected, managed and processed in reasonable time by the software tools that are currently part of the mainstream of tools. Harvard Social ProfessorGary King describes the Big Data Age as “a revolution in which huge data resources have led to quantification in all areas, whether academia, business, or government.†However, Big Data has not yet popularized landscape design. For this reason, one emerging research topic has been to promote the development of the creative park landscape using the resources and favorable information provided by Big Data.
Keywords: Large data, optimization, 3D model, virtual landscape; large data volume; 3D model optimization; data conversion; roaming.
Cite As
Z. Lan, M. Chen, "3D Model Optimization and Roaming of Large Data Volume Virtual Landscape", Â Engineering Intelligent Systems, vol. 26 no. 1, pp. 5-10, 2018.