Parameter-driven Level of Detail Derivation Method for Semantic Building Facade Model

The relentless progress in the research of geographic spatial data models and their application scenarios is propelling an unprecedented rich Level of Detail(LoD)in realistic 3D representation and smart cities.This pursuit of rich details not only adds complexity to entity models but also poses significant computational challenges for model visualization and 3D GIS.This paper introduces a novel method for deriving multi-LOD models,which can enhance the efficiency of spatial computing in complex 3D building models.Firstly,we extract multiple facades from a 3D building model(LoD3)and convert them into individual semantic facade models.Through the utilization of the developed facade layout graph,each semantic facade model is then transformed into a parametric model.Furthermore,we explore the specification of geometric and semantic details in building facades and define three different LODs for facades,offering a unique expression.Finally,an innovative heuristic method is introduced to simplify the parameterized facade.Through rigorous experimentation and evaluation,the effectiveness of the proposed parameterization methodology in capturing complex geometric details,semantic richness,and topological relationships of 3D building models is demonstrated.

An Interactive platform for low-cost 3D building modeling from VGI data using convolutional neural network

The applications of 3D building models are limited as producing them requires massive labor and time costs as well as expensive devices.In this paper,we aim to propose a novel and web-based interactive platform,VGI3D,to overcome these challenges.The platform is designed to reconstruct 3D building models by using free images from internet users or volunteered geographic informa-tion(VGI)platform,even though not all these images are of high quality.Our interactive platform can effectively obtain each 3D building model from images in 30 seconds,with the help of user interaction module and convolutional neural network(CNN).The user interaction module provides the boundary of building facades for 3D building modeling.And this CNN can detect facade elements even though multiple architectural styles and complex scenes are within the images.Moreover,user interaction module is designed as simple as possible to make it easier to use for both of expert and non-expert users.Meanwhile,we conducted a usability testing and collected feedback from participants to better optimize platform and user experience.In general,the usage of VGI data reduces labor and device costs,and CNN simplifies the process of elements extraction in 3D building modeling.Hence,our proposed platform offers a promising solution to the 3D modeling community.

Automatic Generation of 3D Building Models with Multiple Roofs

Based on building footprints (building polygons) on digital maps, we are proposing the GIS and CG integrated system that automatically generates 3D building models with multiple roofs. Most building polygons’ edges meet at right angles (orthogonal polygon). The integrated system partitions orthogonal building polygons into a set of rectangles and places rectangular roofs and box-shaped building bodies on these rectangles. In order to partition an orthogonal polygon, we proposed a useful polygon expression in deciding from which vertex a dividing line is drawn. In this paper, we propose a new scheme for partitioning building polygons and show the process of creating 3D roof models.