行政院國家科學委員會專題研究計畫 成果報告
雷射掃描點雲資料結構化作業分析、幾何品質評估及應用領
域之研究(I)
計畫類別： 個別型計畫
計畫編號： NSC93-2211-E-002-054-
執行期間： 93 年 08 月 01 日至 94 年 10 月 31 日
執行單位： 國立臺灣大學土木工程學系暨研究所
計畫主持人： 趙鍵哲
報告類型： 精簡報告
報告附件： 出席國際會議研究心得報告及發表論文
處理方式： 本計畫可公開查詢
中 華 民 國 95 年 2 月 27 日
( )
(a).
; (b). (Iterated Hough Transform)
(3D Line Features) (Spatial Similarity Transformation)
Abstract
The authors investigated in this study by exploiting the concepts of structuralization on LIDAR point cloud and registering laser scanning data sets from different stations. The former task conducted by two streams includes extracting planes as well as line features and point features derivation. One of the two methods is to table the LIDAR point cloud attributed with geometric and topologic relationship of the points within near neighborhood and thus be able to classify the point cloud into planar features. Line features and point features are then derived seeking neighboring planes. The other method is to employ 3D grid structure well addressing point cloud into 3-D topology and followed by (a). region growing for hypothesizing planes and (b). iterated Hough Transform for refining the plane-features. Line features and point features can then be derived based on the previous solution on plane extraction. The latter task is mainly focused on developing the algorithms in which 3D line feature correspondences for registering multiple data sets with overlapping scene can be established by using geometric constraints in an automatic fashion. The spatial similarity transformation can then be performed by matched 3D line feature correspondence.
Keywords: Structuralization; Region Growing; Iterated Hough Transform; 3D Line Features; Spatial Similarity Transformation
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; Shaker(2004) LBTM(Line Based Transformation Model) Habib et al.(2005)
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21 A B 7(A) 7(B) 7(C) 7(D) 21 21 21
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