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|Title:||Texture mapping of 3-D building models using pose estimation of digital photographs||Authors:||Tan, Y.K.A.
|Issue Date:||2008||Citation:||Tan, Y.K.A.,Kwoh, L.K.,Ong, S.H. (2008). Texture mapping of 3-D building models using pose estimation of digital photographs. 29th Asian Conference on Remote Sensing 2008, ACRS 2008 1 : 593-598. ScholarBank@NUS Repository.||Abstract:||A virtual 3-D city is a sophisticated application of geo-informatics systems as it is a representation of layouts, activities and functionalities of a real-world community. It is an integrated effort in the fields of computer graphics, remote sensing and engineering to model the appearance and dynamics of the real world. The primary aim is to introduce a feasible, yet compelling representation of the city in the virtual world. It will be an attractive option to view and explore the building architecture of the past, present and future without being encumbered by the constraints of reality. Visualization of city models in a virtual environment is a combination of many challenging and laborious tasks, one of which is the texturing of building models façade. To improve the overall photo-realistic quality and usability of the visualization platform, we can texture the building façade with oblique-view terrestrial digital photographs taken using commercially available cameras. This paper will show that we can automatically extract the building façade textures after pose estimation of the acquired image is done. The OpenGL camera must be properly initialized with the intrinsic parameters of the actual camera before pose estimation. After which the actual camera's location and orientation can be estimated directly by matching the relative pose between the rendered 3-D scene geometry and the information from the acquired image. It is important to obtain a good estimate of the camera's pose as the recovered parameters would affect the accuracy of extracted façade textures. A test example will be used to demonstrate the system of performing texture mapping using series of close-range photographs after pose estimation was carried out.||Source Title:||29th Asian Conference on Remote Sensing 2008, ACRS 2008||URI:||http://scholarbank.nus.edu.sg/handle/10635/71961||ISBN:||9781615676156|
|Appears in Collections:||Staff Publications|
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