Abstract
Abstract. 3D city model is a representation of urban area in digital format that contains building and other information. The current approaches are using photogrammetry and laser scanning to develop 3D city model. However, these techniques are time consuming and quite costly. Besides that, laser scanning and photogrammetry need professional skills and expertise to handle hardware and tools. In this study, videogrammetry is proposed as a technique to develop 3D city model. This technique uses video frame sequences to generate point cloud. Videos are processed using EyesCloud3D by eCapture. EyesCloud3D allows user to upload raw data of video format to generate point clouds. There are five main phases in this study to generate 3D city model which are calibration, video recording, point cloud extraction, 3D modeling and 3D city model representation. In this study, 3D city model with Level of Detail 2 is produced. Simple query is performed from the database to retrieve the attributes of the 3D city model.
Highlights
Videogrammetry technique is one of the technique that can be used to get 3-Dimensional (3D) information of an object
The aim of this study is to study videogrammetry technique in developing 3D city model
Based on the resulting point clouds, the number of points are varied because it depends on the area of building being measured and disturbances such as trees and leaves
Summary
Videogrammetry technique is one of the technique that can be used to get 3-Dimensional (3D) information of an object. A set of cameras were used to get spatial data for videogrammetry technique. Decision making time can be reduced by using videogrammetry and the complexity of data processing for infrastructure spatial data can be minimized. This technique gives permission to user during data scanning to move the camera for time-dependent imaging. Due to its ability to capture millions of pixels, videogrammetry gained attention because of its high resolution of video sensors (Ioannis Brilakis et al, 2011). Video sequence (videogrammetry) is able to give more valuable information that can help in processing. Post processing is done where small portion of video frames is selected to get gratification result (Abbas Rashidi et al, 2013)
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