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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Method for Texture Mapping of In-Vehicle Camera Image in 3D Map Creation

Author 1: Kohei Arai

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2019.0101004

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 10, 2019.

  • Abstract and Keywords
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Abstract: Method for texture mapping of in-vehicle camera image in 3D map creation is proposed. Top view of ground cover targets can be mapped easily. For instance, aerial photos, high spatial resolution of satellite imagery data allows creation of top view of ground cover targets and also map creation. It can be used for pedestrian navigations. On the other hand, side view of ground cover targets is not so easy to obtain. In this paper, two methods are proposed. One is to use acquired photos with cameras mounted on the dedicated cars. The other one is to use high spatial resolution of satellite imagery data, such as IKONOS, Orbview, etc. Through experiments with the aforementioned two methods, it is found that texture mapping for the ground cover targets can be done with the two proposed methods in an efficient manner.

Keywords: Texture mapping; high spatial resolution of satellite imagery data; 3D map

Kohei Arai, “Method for Texture Mapping of In-Vehicle Camera Image in 3D Map Creation” International Journal of Advanced Computer Science and Applications(IJACSA), 10(10), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0101004

@article{Arai2019,
title = {Method for Texture Mapping of In-Vehicle Camera Image in 3D Map Creation},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0101004},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0101004},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {10},
author = {Kohei Arai}
}


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