计算机辅助设计与图形学学报
計算機輔助設計與圖形學學報
계산궤보조설계여도형학학보
Journal of Computer-Aided Design & Computer Graphics
2015年
9期
1743-1749
,共7页
胡立华%张继福%张素兰%李晓明
鬍立華%張繼福%張素蘭%李曉明
호립화%장계복%장소란%리효명
摄像机标定%畸变参数估计%单应矩阵%单幅图像%畸变误差
攝像機標定%畸變參數估計%單應矩陣%單幅圖像%畸變誤差
섭상궤표정%기변삼수고계%단응구진%단폭도상%기변오차
camera calibration%distortion parameters estimation%homography%single image%distortion error
摄像机畸变参数估计是摄像机标定的重要步骤. 针对已有的摄像机畸变估计方法大多数为首先对无畸变下的摄像机参数进行标定, 再进一步估计畸变参数, 导致畸变参数估计过程复杂的问题. 采用单应矩阵直接估计畸变参数, 提出一种基于单幅图像的摄像机畸变参数估计算法. 首先利用图像主点附近的图像特征点估计空间平面到图像平面的单应矩阵, 然后利用该单应矩阵估计图像畸变误差和畸变参数, 最后采用非线性优化算法对单应矩阵与畸变参数进行整体优化. 模拟数据与实际图像的实验结果验证了本文算法的有效性; 由于该算法仅需要 1 幅图像即可估计畸变参数, 因此有效地提高了摄像机标定方法的灵活性.
攝像機畸變參數估計是攝像機標定的重要步驟. 針對已有的攝像機畸變估計方法大多數為首先對無畸變下的攝像機參數進行標定, 再進一步估計畸變參數, 導緻畸變參數估計過程複雜的問題. 採用單應矩陣直接估計畸變參數, 提齣一種基于單幅圖像的攝像機畸變參數估計算法. 首先利用圖像主點附近的圖像特徵點估計空間平麵到圖像平麵的單應矩陣, 然後利用該單應矩陣估計圖像畸變誤差和畸變參數, 最後採用非線性優化算法對單應矩陣與畸變參數進行整體優化. 模擬數據與實際圖像的實驗結果驗證瞭本文算法的有效性; 由于該算法僅需要 1 幅圖像即可估計畸變參數, 因此有效地提高瞭攝像機標定方法的靈活性.
섭상궤기변삼수고계시섭상궤표정적중요보취. 침대이유적섭상궤기변고계방법대다수위수선대무기변하적섭상궤삼수진행표정, 재진일보고계기변삼수, 도치기변삼수고계과정복잡적문제. 채용단응구진직접고계기변삼수, 제출일충기우단폭도상적섭상궤기변삼수고계산법. 수선이용도상주점부근적도상특정점고계공간평면도도상평면적단응구진, 연후이용해단응구진고계도상기변오차화기변삼수, 최후채용비선성우화산법대단응구진여기변삼수진행정체우화. 모의수거여실제도상적실험결과험증료본문산법적유효성; 유우해산법부수요 1 폭도상즉가고계기변삼수, 인차유효지제고료섭상궤표정방법적령활성.
The estimation of camera distortion parameters is an important step in the whole camera calibra-tion process, which will directly affect the accuracy of subsequent visual measurement and 3D reconstruc-tion. Currently the distortion estimation in most of the existing calibration methods in the literature is done in a two-step scheme: Firstly the pinhole model is assumed and calibrated, then the distortion parameters are determined. In this work, a homography based method is proposed which could estimate the distortion pa-rameters without resorting to a prior pinhole model estimation step. Our proposed method at first compute the homography from the space plane to the image plane using image feature points around the camera's principal point, by which image distortion errors and distortion parameters are then computed, and a nonlin-ear optimization step is finally employed to simultaneously estimate both the homography and the distortion parameters. The effectiveness of our proposed method is demonstrated by both simulation and real image experiment. Since the proposed method needs only a single image for estimating the distortion parameters, it can significantly enhance the flexibility of camera calibration.