Abstract

Abstract. 3D city model is a digital representation of the Earth’s surface and it’s related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can’t do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city reconstruction; CityEngine is a good product. Agisoft Photoscan software creates much better 3D model with good texture quality and automatic processing. So this image based comparative study is useful for 3D city user community. Thus this study will provide a good roadmap for geomatics user community to create photo-realistic virtual 3D city model by using image based techniques.

Highlights

  • At present scenario, there are four main image based techniques available to create virtual 3D city model

  • The main purpose of this paper is to find out the suitable software for 3D city modeling project

  • The civil engineering department surrounded by department of earth science, department of architecture, department of water resources development and management (WRD&M), and this civil engineering department (CED) has the following main sections and buildings: Geomatics section building, Geotechnical section building, Lecture hall building, Wind engineering section, O.P

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Summary

INTRODUCTION

There are four main image based techniques available to create virtual 3D city model. Till date, there is a no perfect comparative study available to study the image based 3D city model. Wang (2011), explained about a comparative study of five 3D modeling systems based on the SfM principles He has taken only four software; Bundler, PMVS2, Project Photofly (Autodesk), and ARC 3D Web Service in their work. The literature study shows that, till date, there is no complete such type of comparative study available for 3D city modeling user community. This research paper will fulfill gap and useful for image based 3D city modeling community. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan software, were explained This comparative study is based on mainly, general overview of software, method of image data acquisition, data processing methods, and result of output 3D model.

STUDY AREA
GENERAL OVERVIEW
COMPARATIVE STUDY BASED ON DATA PROCESSING:
COMPARATIVE STUDY BASED ON OUTPUT 3D MODEL
STRENGTHS AND WEAKNESS
Photographs
The most beauty of this software is: both image alignment and
It works for convergent photography with high overlapping
Dimension values
10. CONCLUSION
Full Text
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