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用於大型環境三維重建之雷射掃描儀與影像感測器自動校正 = Automat...
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國立高雄大學資訊工程學系碩士班
用於大型環境三維重建之雷射掃描儀與影像感測器自動校正 = Automatic Calibration of LiDAR and Stereo Camera System for 3-D Reconstruction of Large Scale Scene
紀錄類型:
書目-語言資料,印刷品 : 單行本
並列題名:
Automatic Calibration of LiDAR and Stereo Camera System for 3-D Reconstruction of Large Scale Scene
作者:
黃柏森,
其他團體作者:
國立高雄大學
出版地:
[高雄市]
出版者:
撰者;
出版年:
2013[民102]
面頁冊數:
111面圖,表格 : 30公分;
標題:
三維重建
標題:
3-D Reconstruction
電子資源:
http://handle.ncl.edu.tw/11296/ndltd/38549608884926359015
附註:
參考書目:面96-100
附註:
102年10月31日公開
摘要註:
雷射掃描儀是近年來廣泛應用之空間量測工具,其可迅速取得大範圍之三維資料。雷射測距雖具有準確與測量迅速之特性,但無法取得色彩資訊,因此需與彩色影像感測器整合,方能獲得彩色的點雲資料。雙眼視覺系統是電腦視覺中常用之深度計算技巧,但由於雙眼視覺系統須仰賴強健之影像特徵,才可有效地進行像素匹配,因此易受環境之條件影響,無法有效傳回稠密之點雲資訊。若結合此二種方法之優點,則能迅速取得彩色之點雲,重建精確的三維模型。本文討論一自動校正方法,將一機動式雷射掃描儀系統與視覺系統整合,建置移動式掃描平台,以達到大型環境的三維場景重建。 本研究之系統整合兩台相機與一台雷射掃描儀以進行大型三維環境重建。首先,根據電腦視覺的三角測量原理,設置兩台固定焦距及曝光等參數且經過光學校正之相機擷取影像。接著,針對兩張擷取的影像作特徵偵測,再進行對兩張影像進行空間上之特徵匹配,並根據其結果求出瞬間之稀疏點雲。同時,隨著時間之推移,兩影像序列分別進行時間上之特徵點追蹤,並透過時空特徵點匹配,算出各時間點之點雲間的旋轉與位移變換,進而推演出掃描平台行進的路徑,將點雲對齊並擴展掃瞄範圍。由視覺系統獲得較完整之環境稀疏點雲後,再以雷射測距掃描儀擷取大型稠密之環境點雲,並與稀疏點雲進行對齊計算,取得兩系統間之外部參數。在實驗結果中,本研究亦使用紅外線影像擷取雷射測距掃描儀的雷射掃描光軌跡並進行分析,將點雲重新投影至影像平面上進而驗證外部參數之精確性。 The Light Detection and Ranging (LiDAR) device has become an increasingly common tool for the acquisition of 3D data. Such devices are capable of acquiring 3D measurement quickly and accurately over relatively large coverage areas. However, a LiDAR device is unable to capture the color information of the surfaces. Binocular stereo, on the other side, can be easily deployed to acquire colored depth data but requires image features to perform correspondence analysis for depth calculation and has difficulties in providing dense depth data. The LiDAR and the binocular stereo systems have complementary characteristics and by integrating the two systems, it is possible to construct a system that possesses the advantages of the two methods. In this work, we constructing a system mounted with a LiDAR device and two pan-tilt cameras for large scale 3D scene reconstruction. Spatial feature detection and matching are then performed on the images to obtain sparse point cloud. As the system moves with time, temporal feature tracking is also performed on the images sequence to calculate intra-frame motion. With the proposed auto-calibration method, the extrinsic parameters of the LiDAR and the cameras are calculated, which are in turn used to align the point clouds scanned by the LiDAR along the path. Experimental results have shown that the proposed system and method is able to achieve integrated dense reconstruction for large scale scene.
用於大型環境三維重建之雷射掃描儀與影像感測器自動校正 = Automatic Calibration of LiDAR and Stereo Camera System for 3-D Reconstruction of Large Scale Scene
黃, 柏森
用於大型環境三維重建之雷射掃描儀與影像感測器自動校正
= Automatic Calibration of LiDAR and Stereo Camera System for 3-D Reconstruction of Large Scale Scene / 黃柏森撰 - [高雄市] : 撰者, 2013[民102]. - 111面 ; 圖,表格 ; 30公分.
參考書目:面96-100102年10月31日公開.
三維重建3-D Reconstruction
用於大型環境三維重建之雷射掃描儀與影像感測器自動校正 = Automatic Calibration of LiDAR and Stereo Camera System for 3-D Reconstruction of Large Scale Scene
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雷射掃描儀是近年來廣泛應用之空間量測工具,其可迅速取得大範圍之三維資料。雷射測距雖具有準確與測量迅速之特性,但無法取得色彩資訊,因此需與彩色影像感測器整合,方能獲得彩色的點雲資料。雙眼視覺系統是電腦視覺中常用之深度計算技巧,但由於雙眼視覺系統須仰賴強健之影像特徵,才可有效地進行像素匹配,因此易受環境之條件影響,無法有效傳回稠密之點雲資訊。若結合此二種方法之優點,則能迅速取得彩色之點雲,重建精確的三維模型。本文討論一自動校正方法,將一機動式雷射掃描儀系統與視覺系統整合,建置移動式掃描平台,以達到大型環境的三維場景重建。 本研究之系統整合兩台相機與一台雷射掃描儀以進行大型三維環境重建。首先,根據電腦視覺的三角測量原理,設置兩台固定焦距及曝光等參數且經過光學校正之相機擷取影像。接著,針對兩張擷取的影像作特徵偵測,再進行對兩張影像進行空間上之特徵匹配,並根據其結果求出瞬間之稀疏點雲。同時,隨著時間之推移,兩影像序列分別進行時間上之特徵點追蹤,並透過時空特徵點匹配,算出各時間點之點雲間的旋轉與位移變換,進而推演出掃描平台行進的路徑,將點雲對齊並擴展掃瞄範圍。由視覺系統獲得較完整之環境稀疏點雲後,再以雷射測距掃描儀擷取大型稠密之環境點雲,並與稀疏點雲進行對齊計算,取得兩系統間之外部參數。在實驗結果中,本研究亦使用紅外線影像擷取雷射測距掃描儀的雷射掃描光軌跡並進行分析,將點雲重新投影至影像平面上進而驗證外部參數之精確性。 The Light Detection and Ranging (LiDAR) device has become an increasingly common tool for the acquisition of 3D data. Such devices are capable of acquiring 3D measurement quickly and accurately over relatively large coverage areas. However, a LiDAR device is unable to capture the color information of the surfaces. Binocular stereo, on the other side, can be easily deployed to acquire colored depth data but requires image features to perform correspondence analysis for depth calculation and has difficulties in providing dense depth data. The LiDAR and the binocular stereo systems have complementary characteristics and by integrating the two systems, it is possible to construct a system that possesses the advantages of the two methods. In this work, we constructing a system mounted with a LiDAR device and two pan-tilt cameras for large scale 3D scene reconstruction. Spatial feature detection and matching are then performed on the images to obtain sparse point cloud. As the system moves with time, temporal feature tracking is also performed on the images sequence to calculate intra-frame motion. With the proposed auto-calibration method, the extrinsic parameters of the LiDAR and the cameras are calculated, which are in turn used to align the point clouds scanned by the LiDAR along the path. Experimental results have shown that the proposed system and method is able to achieve integrated dense reconstruction for large scale scene.
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http://handle.ncl.edu.tw/11296/ndltd/38549608884926359015
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