图像序列中机动目标三维运动和结构的计算

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

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。

The paper presents a 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 the displacement field. The paper also estimates 3D motion and structure from optical flow in image sequence. The implementation of a non-linear algorithm is described, whose uniform observability, minimal realization and stability are proved analytically. Experimental results show that the method provides a good estimation of the optical flow and 3D motion and structure.