Abstract: Optical flow estimation is an important method to motion image analysis. This paper introduces forward and backward constraint equation and Hessian matrix for the computation of optical flow. It examines well-posedness of each point of local neighbourhood and the weight of Lucas－Kanade’s method is defined as the reciprocal of the conditioning number of its Hessian Matrix. This can eliminate those uncertainty constrains and improve the numerical stability of the solution of the gradient constraint equation. Experimental results show that this method is suitable and reliable.

Key words: Optical flow, Hessian matrix, Conditioning number

摘要： 光流法是运动图像序列分析的一种重要方法。该文通过引入前向－后向光流方程，计算其Hessian矩阵，把Hessian矩阵条件数的倒数作为Lucas－Kanade光流法的加权阵，可有效消除局部邻域中不可靠约束点，同时提高基本约束方程解的稳定性。实验表明该方法相对于其它梯度约束光流法具有更好的可靠性。

关键词: 光流, Hessian矩阵, 条件数