Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery
碩士 === 國立臺灣大學 === 土木工程學研究所 === 105 === Stereo matching can effectively produce dense point cloud, but it may encounter great challenge when faced with low-textured image content. Even added with artificial texture, the location of the targeted scene, operation condition, and hardware requirement, am...
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ndltd-TW-105NTU050150642019-05-15T23:39:38Z http://ndltd.ncl.edu.tw/handle/73v7m5 Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery 以人工紋理協助弱紋理區影像三維重建 Wan-Ting Chen 陳婉婷 碩士 國立臺灣大學 土木工程學研究所 105 Stereo matching can effectively produce dense point cloud, but it may encounter great challenge when faced with low-textured image content. Even added with artificial texture, the location of the targeted scene, operation condition, and hardware requirement, among others, still demand considerable concerns to arrange for appropriate work scheme. This work captures images by low cost projectors and a camera, and dense matching software SURE is used to generate 3D point clouds. Regarding how and what to project textures, the main focus is on analyzing and designing suitable textures taking the surface, geometry, and making succession of scene into consideration. On the other hand, the fine placements of projectors and camera stations are also crucial to maintaining quality imaging geometry. The four main parameters for image acquisition, baseline, object distance, principal distance, and f-number can be determined by the required accuracy for 3D reconstruction. This study establishes appropriate work steps and rules for reconstructing low texture scene, and the experiments validate its effectiveness and applicability meeting quality requirement. 趙鍵哲 2017 學位論文 ; thesis 110 zh-TW |
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碩士 === 國立臺灣大學 === 土木工程學研究所 === 105 === Stereo matching can effectively produce dense point cloud, but it may encounter great challenge when faced with low-textured image content. Even added with artificial texture, the location of the targeted scene, operation condition, and hardware requirement, among others, still demand considerable concerns to arrange for appropriate work scheme. This work captures images by low cost projectors and a camera, and dense matching software SURE is used to generate 3D point clouds. Regarding how and what to project textures, the main focus is on analyzing and designing suitable textures taking the surface, geometry, and making succession of scene into consideration. On the other hand, the fine placements of projectors and camera stations are also crucial to maintaining quality imaging geometry. The four main parameters for image acquisition, baseline, object distance, principal distance, and f-number can be determined by the required accuracy for 3D reconstruction. This study establishes appropriate work steps and rules for reconstructing low texture scene, and the experiments validate its effectiveness and applicability meeting quality requirement.
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author2 |
趙鍵哲 |
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趙鍵哲 Wan-Ting Chen 陳婉婷 |
author |
Wan-Ting Chen 陳婉婷 |
spellingShingle |
Wan-Ting Chen 陳婉婷 Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
author_sort |
Wan-Ting Chen |
title |
Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
title_short |
Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
title_full |
Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
title_fullStr |
Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
title_full_unstemmed |
Using Artificial Texture to Assist 3D Reconstruction ofLow Texture Imagery |
title_sort |
using artificial texture to assist 3d reconstruction oflow texture imagery |
publishDate |
2017 |
url |
http://ndltd.ncl.edu.tw/handle/73v7m5 |
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