光達點雲幾何特徵萃取及匹配

Multi-feature Based Registration of LiDAR Point Clouds

莊子毅(Tzu-Yi Chuang) ； 趙鍵哲(Jen-Jer Jaw)

《航測及遙測學刊》 20卷2期 (2016/04) Pp. 109-128

https://doi.org/10.6574/JPRS.2016.20(2).3

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。

關鍵字

光達點雲 ； 幾何特徵 ； 特徵萃取 ； 特徵匹配

並列摘要

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.

並列關鍵字

LiDAR ； multiple features ； feature extraction ； feature matching