基于光流的运动人体提取

提出了一种改进的Lucas-Kanade光流算法，将这种算法应用于步态识别中, 并引入了高阶梯度的光流场约束方程，计算出其Hessian矩阵. 将Hessian矩阵条件数的倒数做为Lucas-Kanade光流法的加权阵，可有效地消除局部邻域中不可靠约束点，并大大提高基本约束方程解的稳定性. 实验结果表明，此方法能精确地描述出运动人体的光流场.

Gait Extraction Based on Optical Flow

An improved technique for Lucas-Kanade optical flow was proposed, which was used in the field of gait recognition. Firstly, a constrained equation of high-order gradient was introduced, and then Hessian matrix can be computed. Secondly, the reciprocal of conditional operators of Hessian matrix was taken as the weighted matrix of Lucas-Kanade flow field. This method can eliminate the unreliable constrained points of local neighborhood, and increase the stability of the basic solution of the constrained equation. The experiment results showed that the proposed method can establish the optical flow field for human gait precisely