1. NCCU Academic Hub
  2. 學術產出
  3. 社會科學學院
  4. 會議論文
  5. Item

學術產出-會議論文

文章檢視/開啟

書目匯出

Google ScholarTM

政大圖書館

引文資訊

TAIR相關學術產出

題名 An algorithm to extract 3-D building roof points from airborne LIDAR data
作者 Chio, Shih-Hong
邱式鴻
貢獻者 地政系
關鍵詞 Aerial images; Airborne lidar data; Building reconstruction; Building roof; Data snooping; Forward selection; Least squares fitting; LIDAR data; Orthoimages; Quad trees; Algorithms; Buildings; Optical radar; Remote sensing; Roofs; Three dimensional; Trees (mathematics)
日期 2006
上傳時間 21-七月-2015 15:08:05 (UTC+8)
摘要 Building roof points in airborne LIDAR data are very important for 3-D building reconstruction. This paper will present an algorithm to automatically acquire the 3-D building roof points from airborne LIDAR data. Firstly, for roughly locating the area outlines of the roof(s) from pure LIDAR data, the aerial images with known orientation and original LIDAR data are used to generate the orthoimages. Then, the user indicates the area outlines of the building(s) on the orthoimages by mouse device. Afterwards, on the assumption that roofs are composed of either horizontal or slope planes, some better plane information, called GRID planes, are extracted by means of least squares fitting based on quad-tree segmentation from the LIDAR data in the area outlines. These GRID planes will be further merged according to the height constraints for providing SEED regions for plane growing by employing forward selection data snooping approach to merging the neighboring roof LIDAR points in order to extract the whole roof points. From the experiments, the efficiency of the proposed algorithm will be shown.
關聯 Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006, Pages 990-996
資料類型 conference
dc.contributor 地政系
dc.creator (作者) Chio, Shih-Hong
dc.creator (作者) 邱式鴻zh_TW
dc.date (日期) 2006
dc.date.accessioned 21-七月-2015 15:08:05 (UTC+8)-
dc.date.available 21-七月-2015 15:08:05 (UTC+8)-
dc.date.issued (上傳時間) 21-七月-2015 15:08:05 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/76750-
dc.description.abstract (摘要) Building roof points in airborne LIDAR data are very important for 3-D building reconstruction. This paper will present an algorithm to automatically acquire the 3-D building roof points from airborne LIDAR data. Firstly, for roughly locating the area outlines of the roof(s) from pure LIDAR data, the aerial images with known orientation and original LIDAR data are used to generate the orthoimages. Then, the user indicates the area outlines of the building(s) on the orthoimages by mouse device. Afterwards, on the assumption that roofs are composed of either horizontal or slope planes, some better plane information, called GRID planes, are extracted by means of least squares fitting based on quad-tree segmentation from the LIDAR data in the area outlines. These GRID planes will be further merged according to the height constraints for providing SEED regions for plane growing by employing forward selection data snooping approach to merging the neighboring roof LIDAR points in order to extract the whole roof points. From the experiments, the efficiency of the proposed algorithm will be shown.
dc.format.extent 176 bytes-
dc.format.mimetype text/html-
dc.relation (關聯) Asian Association on Remote Sensing - 27th Asian Conference on Remote Sensing, ACRS 2006, Pages 990-996
dc.subject (關鍵詞) Aerial images; Airborne lidar data; Building reconstruction; Building roof; Data snooping; Forward selection; Least squares fitting; LIDAR data; Orthoimages; Quad trees; Algorithms; Buildings; Optical radar; Remote sensing; Roofs; Three dimensional; Trees (mathematics)
dc.title (題名) An algorithm to extract 3-D building roof points from airborne LIDAR data
dc.type (資料類型) conferenceen