ENGLISH

20卷/2期

20卷/2期

華藝線上圖書館

Pages:

75-92

論文名稱

GSM法-從空載光達點雲萃取道路交通標線交點

Title

GSM Method for Extraction of Intersection Points of Road Marking Lines from Airborne LiDAR Point Clouds

作者

李宏君, 蔡展榮

Author

Hong-Chun Li, Jaan-Rong Tsay

中文摘要

本文根據瀝青路面及道路交通標線之光達回波強度的差異性,設計高斯曲面匹配(Gaussian Surface Matching, GSM)法,以求定直線型交通標線之線特徵參數,進而求得垂直交會的兩條直線標線之交點,並由不同航帶的光達點雲同名交點來估計與改正相鄰航帶點雲坐標基準偏差量,俾使用標線交點群來求解空照影像的外方位元素,使兩者建立在共同的坐標系統之中,以利後續空載光達與航空攝影測量的整合應用。經由實際資料測試,光達航帶點雲坐標基準經改正後,同名交點之整體平面偏差量之均方根值從0.650m降至0.286m,符合光達點之先驗平面精度±0.25m。使用這些基準改正後的點位做為地控點(共30點),施行空照影像光束法平差,整體空三精度達到±0.67個像元的次像元精度等級。

Abstract

Real airborne LiDAR data show that the laser intensity on asphalt surface is significantly lower than the one on road marking lines. A Gaussian Surface Matching (GSM) approach is thus developed and presented to determine the parameters of road marking lines and the coordinates of the intersection of two road marking lines as well. Those intersections in the overlapping scanning areas of two neighboring LiDAR strips can be then applied to evaluate the related systematic bias. After systematic bias estimation and correction, the root mean square registration error is reduced from 0.650m to 0.286m in horizontal direction. These intersections are then used as ground control points in aero triangulation (AT). The AT with the precision of ±0.67 pixel is generated.

關鍵字

高斯曲面匹配法、空載光達、空照數位影像、反射強度

Keywords

gaussian surface matching, airborne LiDAR, aerial digital image, reflectance

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

93-108

論文名稱

以多尺度萃取方法進行車載光達資料之類桿狀道路物件重建

Title

Pole-like Road Object Extraction from Mobile Lidar System Based on Multi-scale Approach

作者

張智安, 邱繼珉

Author

Tee-Ann Teo, Chi-Min Chiu

中文摘要

車載光達系統(Mobile Lidar System, MLS)行駛在道路上以直接地理對位(Direct Georeferencing)方式進行雷射掃描,能夠快速獲取三維道路資訊進行道路調查,然而車載光達系統因資料量龐大及盲資料(Blind data)的特性,在應用上有許多挑戰。本研究發展車載光達資料自動化道路類桿狀物件重建方法,道路類桿狀物件包含路燈、交通號誌、及行道樹等。本研究採取模型導向重建策略,主要工作包含:(1)資料前處理、(2)類桿狀道路物件點雲偵測、及(3)物件點雲分類。資料前處理部分,對原始點雲進行分段分割並濾除路廊兩側牆面點雲;類桿狀道路物件點雲偵測部分,本文提出一個多尺度分割方法(Multi-scale Segmentation),包含體元(Voxel)尺度分割、點(Point)尺度分割及混合物分割三階段;物件點雲分類採取知識庫分類方法(Knowledge-based Classification)辨識出物件點雲所屬類別。研究成果顯示,在偵測階段成功率為95%,道路物件分類整體精度為72%,重建桿狀物件中心之位置精度在10公分以內,因此,所提出的方法可有效應用於車載光達之類桿狀道路物件重建。

Abstract

Mobile lidar system (MLS) which acquires detailed and accurate 3D point clouds along road corridors can assist traditional road inventory work. However, the blind characteristics and the huge amount of point clouds still make it difficult for applications. Therefore, an automatic process for MLS is required. The objective of this study is to develop a novel approach for pole-like road objects extraction from MLS data. The pole-like road objects consist of street light, traffic light, trees, etc. The proposed framework is a model-driven approach. The major work contains three parts: (1) data pre-processing, (2) pole-like object detection, and (3) object classification. In data pre-processing, the raw data are partitioned into several road parts and the building façade aside road are removed to avoid mis-classification. In object detection, a multi-scale segmentation is presented to detect pole-like road objects. Finally, the knowledge-based approach is used to classify pole-like road objects. The experiments demonstrate that the correctness of detection is about 95% and the overall accuracy of classification reaches 72%. The positional accuracy of pole-like object reconstruction is better than 0.1 meters. The results indicate that the method can extract pole-like road objects from MLS data effectively.

關鍵字

車載光達系統、道路調查、分類、重建

Keywords

mobile LiDAR system, road inventory, classification, reconstruction

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

109-128

論文名稱

光達點雲幾何特徵萃取及匹配

Title

Multi-feature Based Registration of LiDAR Point Clouds

作者

莊子毅, 趙鍵哲

Author

Tzu-Yi Chuang, Jen-Jer Jaw

中文摘要

光達感測器隨著在掃描速率、測程及定位精度方面的效能提升,儼然已成為三維空間資訊蒐集技術的主流。光達系統載具平台具備空載、車載與靜態地面掃描三種形式因應不同測繪需求,而為建構完整場景描述與獲取多時期資料整合之加值效益,點雲資料套合即為重要的前端處理程序之一。點雲資料套合作業倘仰賴人工進行控制標布設或共軛特徵量測,在執行效率與成本上往往未能獲得最佳效益。基於此,為提升點雲套合前置作業效能,本研究研擬自動化方式萃取光達點雲中點、直線與平面三種基本幾何元件,並考量特徵品質以及在滿足套合轉換模式下完成共軛特徵對應。實驗成果顯示,本研究建構之特徵萃取及匹配演算法可獲致良好的共軛特徵對應,匹配過程所計算的轉換參數估值則可逕行點雲套合任務或作為嚴密套合的良好初始值。

Abstract

Recently, as the continuing improvements in laser sensors with respect to the scanning rate, ranging limit, resolution, accuracy and systemic efficacy, LiDAR has evolved as a major technique for rapid 3-D geo-information acquisition and also led to many new and fascinating applications of a board range of fields. In regard to LiDAR data processing, registration of point clouds scanned from different stations and platforms is one of essential prerequisites for a uniformity of data quality or forming complete scenes. However, the current ways of registration are mostly achieved by using control targets and require a lot of human intervention. Therefore, there still remains a great room for bettering the registration task with less labor consume, high efficiency and good quality. Moreover, how to obtain concrete 3-D information from discrete point clouds is also an important issue. Thus, this paper presents a multiple feature extractor and a novel feature matching approach to realize an automated scheme in feature extraction and pairing among LiDAR point clouds. With the successful demonstrations, the combination of the multiple feature extractor and matcher has been verified as a satisfactory working technique to conduct a variety of LiDAR point clouds

關鍵字

光達點雲、幾何特徵、特徵萃取、特徵匹配

Keywords

LiDAR, multiple features, feature extraction, feature matching

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

129-137

論文名稱

應用多視立體及運動回復結構之三維場景重構

Title

Application of Multi-View Stereo and Structure from Motion to 3D Scene Reconstruction

作者

趙智凡, 潘偉庭, 楊明德

Author

Chih-Fan Chao, Wei-Ting Pan, Ming-Der Yang

中文摘要

三維場景重構能應用於多領域做分析、展示。本研究運用電腦視覺相關演算法,如運動回復結構(Structure from Motion, SfM)、群集觀點多視立體(Clustering Views for Multi-View Stereo, CMVS)、以區塊為基礎之多視立體(Patch-Based Multi-View Stereo, PMVS)、柏松表面重構(Poisson surface reconstruction, PSR),透過多張影像重構三維場景模型。本研究使用消費型相機與智慧型裝置拍攝不同物體角度之影像,不需要額外提供攝影裝備的內外參數,即能重構室內外各種尺度的模型,物件由小到大分別為安全帽、水泥方柱、室外涼亭,以及UAV空拍中興大學,並評估各模型的焦距精度。最後,重構三種不同的水泥方柱模型,利用圖標長度來還原模型真實尺度並進行體積評估。

Abstract

3D scene reconstruction has been applied to broad fields to analyze complex 3D information and display 3D models. The study applies computer vision algorithms, including Structure from Motion (SfM), Clustering Views for Multi-View Stereo (CMVS), Patch-based Multi-View Stereo (PMVS), and Poisson Surface Reconstruction (PSR) to generate 3D scene models with numerous images. This study employs images taken by commercial cameras and smart devices for 3D scene reconstruction through aforesaid algorithms without the need of internal and external parameters. Also, 3D models can be reconstructed in different scales, such as both indoor and outdoor for example. There are four experimental objects containing the helmet and the concrete pillar as small scale models, the pavilion outdoor as a middle scale model, and National Chung Hsing University’s campus as a large scale model to estimate accuracy of focal lengths for 3D models respectively. Finally, reconstructing three different types of concrete pillars and applying constraint rules of a pattern scale was executed to recover the real scale models for volume estimation.

關鍵字

三維場景重構、特徵萃取、電腦視覺、多視立體

Keywords

3D scene reconstruction, feature extraction, computer vision, multi-view stereo

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

Pages:

139-150

論文名稱

三維空間資訊於建築物火災搶救模擬之應用

Title

3D Spatial Information for Fire-Fighting Simulation of Building Fires

作者

吳家豪, 陳良健

Author

Chia-Hao Wu, Liang-Chien Chen

中文摘要

消防單位已使用地理資訊系統以縮短緊急事故之反應時間。然而,起火建築物內部之複雜結構將使得火災搶救及人命救助工作在緊急情況下更加困難。本研究乃基於一個微型地理資訊系統以分析及展示三維空間資訊用於建築物火災消防搶救模擬。首先,從二維建築圖中產生三維幾何網路模型用於室內之路網分析。其次,應用建築資訊模型於地理資訊環境中以提供一個具幾何與語意資訊之三維可視化虛擬環境。此外,加入雲梯車於三維環境中以模擬雲梯車之佈署及操作。最後,本研究乃用於執行一個真實建築物火災搶救之模擬。本研究可以提供消防人員尋找建築物內部之最短安全救援路徑,且幫助消防人員迅速佈署雲梯車,以縮短緊急應變之反應時間。

Abstract

Fire departments already make use of geographic information systems (GIS) to reduce the response time in case of incidents. However, the complex internal structure of buildings on fire may make search and rescue efforts difficult in emergency situations. This study was motivated by the need for a micro GIS to represent and analyze 3D spatial data for fire-fighting simulations of building fires. A method was developed to generate a 3D geometric network model (GNM) from 2D building plans. This model performed network-based analysis within a building. In addition, the applicability of the building information model (BIM) in geospatial environments could provide a 3D visualization environment with sufficient geometric and semantic information about the buildings. Virtual ladder trucks were added in the 3D environment to simulate the positioning and operations of aerial ladders. Finally, the GNM model was implemented to perform fire-fighting simulations based on actual buildings. The proposed method can provide a tool to assist firefighters to find the optimal path within a building, minimize the search time for potential victims, and help firefighters quickly locate their ladder trucks, so as to reduce the response time after an incident.

關鍵字

地理資訊系統、建築資訊模型、緊急應變

Keywords

geographic information system, building information model, emergency response

附件檔名

華芸線上圖書館

N / A

備註說明

N / A

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