Dept. of Syst. and Inf., Florence Univ.
IEEE Trans Image Process. 1996;5(5):720-39. doi: 10.1109/83.495956.
Several approaches for optical flow estimation use partial differential equations to model changes in image brightness throughout time. A commonly used equation is the so-called optical flow constraint (OFC), which assumes that the image brightness is stationary with respect to time. More recently, a different constraint referred to as the extended optical flow constraint (EOFC) has been introduced, which also contains the divergence of the flow field of image brightness. There is no agreement in the literature about which of these constraints provides the best estimation of the velocity field. Two new solutions for optical flow computation are proposed, which are based on an approximation of the constraint equations. The two techniques have been used with both EOFC and OFC constraint equations. Results achieved by using these solutions have been compared with several well-known computational methods for optical flow estimation in different motion conditions. Estimation errors have also been measured and compared for different types of motion.
几种用于光流估计的方法使用偏微分方程来模拟图像亮度随时间的变化。一个常用的方程是所谓的光流约束(OFC),它假设图像亮度相对于时间是静止的。最近,引入了一种不同的约束,称为扩展光流约束(EOFC),它也包含了图像亮度流场的散度。在文献中,对于哪种约束能提供最佳的速度场估计,并没有达成一致意见。提出了两种基于约束方程近似的新的光流计算解决方案。这两种技术都已应用于 EOFC 和 OFC 约束方程。使用这些解决方案获得的结果与不同运动条件下几种著名的光流估计计算方法进行了比较。还测量和比较了不同类型运动的估计误差。