航空学报 > 2004, Vol. 25 Issue (1): 55-58

图像序列中机动目标三维运动和结构的计算

陈震1, 高满屯2, 杨声云1, 沈允文2   

  1. 1. 南昌航空工业学院人工智能与图像处理研究中心, 江西南昌 330034;2. 西北工业大学机电工程学院, 陕西西安 710072
  • 收稿日期:2002-11-12 修回日期:2003-05-06 出版日期:2004-02-25 发布日期:2004-02-25

Calculation of 3D Motion and Structure from Optical Flow in Image Sequence

CHEN Zhen1, GAO Man-tun2, Yang Sheng-yun1, SHEN Yun-wen2   

  1. 1. The Center of Artificial Intelligence and Image Processing, Nanchang Institute of Aeronautical Technology, Nanchang 330034, China;2. College of Mechanical and Electrical Engineering, Northwestern Polytechnical University, Xi'an 710072, China
  • Received:2002-11-12 Revised:2003-05-06 Online:2004-02-25 Published:2004-02-25

摘要: 综合视觉运动分析中的2类处理方法,选取图像中的角点作为特征点,在理论上证明了图像序列的光流场可以近似地用角点的位移场代替。利用已有文献中的建模思想,详细推导出递归计算机动目标三维运动和结构的非线性计算模型,采用广义卡尔曼滤波(EKF)递归地计算图像序列中机动目标的三维运动和结构。合成图像序列和真实图像序列实验结果表明该算法能取得较好的效果。

关键词: 光流场, 角点位移场, 广义卡尔曼滤波, 三维运动和结构, 图像序列, 计算机视觉

Abstract: The paper presents a new method for optical flow estimating, which combines feature based with flow based method. By using the corner points as feature points and estimating the optical flow from image sequence, the optical flow is estimated by measuring the displacement of sparse located corner points between consecutive frames. It is proved theoretically that optical flow can be replaced approximately by using the displacement field. The paper also estimates 3D motion and structure from optical flow in image sequence. In this paper, the implementation of a non-linear algorithm is described,whose uniform observability, minimal realization and stability are proved analytically. Experimental results show that the new method provide a good estimation of the optical flow and 3D motion and structure.

Key words: computer vision, optical flow, corner point displacement field, extended Kalman filter, 3D motion and structure, image sequence