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基于序列影像的小天体三维形状重建方法研究
蓝朝桢1,2, 耿迅1, 徐青1, 崔平远2
1.信息工程大学地理空间信息学院,郑州450052;2.北京理工大学深空探测技术研究所,北京100081
摘要:
提出了一种基于序列影像的小天体三维形状重建方法。利用小天体序列影像间的内在几何约束关 系,在无精确位置、姿态数据的条件下,基于稀疏光束法平差求解小天体序列影像的相对位置、姿态。综合利用核 线几何约束、半全局匹配、多视最小二乘匹配等策略进行小天体序列影像的密集匹配,重建小天体三维形状信息。 由于小天体序列影像尺度变化大、纹理贫乏,导致影像匹配的误匹配率较高,在匹配过程中采用随机KD树搜索策 略与拟合透视变换模型的RANSAC算法剔除粗差。利用“黎明号”探测器的绕飞段实测影像,对灶神星(VESTA) 的三维形状重建进行了实验,结果证明了该方法的有效性。
关键词:  小天体;三维重建;深空探测;密集匹配;序列影像
DOI:
分类号:P234
基金项目:国家重点基础研究发展计划(973计划)(2012CB720000);中国博士后基金资助(2013M540870)
3D Shape Reconstruction for Small Celestial Body Based on Sequence Images
LAN Chaozhen1,2, GENG Xun1, XU Qing1, CUI Pingyuan2
1.Institute of Surveying and Mapping,Information Engineering University,Zhengzhou450052,China;2.Institute of Deep Space Exploration Technology,Beijing Institute of Technology,Beijing100081,China
Abstract:
A method for 3D shape reconstruction of small celestial body based on sequence images is proposed.Using the internal geometric constraints of sequence images,the relative position and attitude parameters of sequence images are estimated based on sparse bundle adjustment.In order to reconstruct the 3D shape of the small celestial body,such solutions as epipolar line geometric constraints,semi-global matching strategy and multi-view least squares matching are combined to perform dense image matching.In order to solve the mis-matching problem caused by the different scale and lack of texture details,the search strategy of random KD tree and RANSAC method with perspective model are used to detect outliers.Then,the 3D shape of VESTA is reconstructed using the method above by sequence images obtained from the Dawn mission.The results demonstrate our method’s effectiveness.
Key words:  small celestial body;3D reconstruction;deep space exploration;dense matching;sequence images