我想学习使用卡尔曼滤波器跟踪移动的球。尽管有很多教程可用，但我仍然有一些问题。
如果我们能在视频序列的每一帧中提取出球，我们就会知道球的位置。那么，为什么我们还需要使用卡尔曼滤波器呢？卡尔曼滤波器在这里的作用是什么？
卡尔曼滤波器：x(k+1) = Ax(k) + Bu(k) + 噪声
y(k) = C.x(k) + noise
那么，我们如何定义 A、B、C 呢？假设我们要跟踪移动的球？
3. 如果我们知道先前状态 x(k-1) 和当前状态 y(k) 的测量值，我们可以计算估计状态。跟踪移动球时的“测量”是什么？
well basically you use tracking method to follow the ball in your scene. You'd still have to detect the ball in each timestep.
(1)
Assume you come to a point where another ball comes into the scene. So you need to find a method to identify each ball. Make it worse and even let them cross each other or have obstacles in the way which might hide the ball for a little while.
Your tracking method (i.e. Kalman filter) will then continue its movement on the estimated trajectory, based on how the ball has moved before.
So if you just want to know where the ball is in each frame you don't need a tracking method, but if yo uwant to identify and follow one ball you'd need a tracker, i.e. a Kalman filter or for multi-object tracking I'd prefer a Particle Filter (http://en.wikipedia.org/wiki/Particle_Filter).
(2)
Can't help you here right now since I am not too far into the Kalman Filter right now. But basically A should be the transition matrix from step x(t-1) to x(t) and B should be the reference model. But as I've said if its likely you get more than one ball you might wanna have a look at the particle filter.
(3)
The measurement would be the position you measured on you image. Basically the midpoint of your ball. You'd use this measurement to correct the estimated path. So basically you compare the position the ball should be at at current timestep (depending on it's former movement) with it's actual position.
I hope that helps... if not, keep asking...
我会一一回答你的问题。
卡尔曼滤波器仅用于估计，它意味着减少错误。当你只是跟踪单个目标时，比如一个球，如果你能确定球在每一帧图像中的位置，我认为没有必要使用卡尔曼滤波器。但是，在多目标跟踪中，如果需要在连续两帧中匹配同一个目标，使用卡尔曼滤波器可以减少错误。
对于卡尔曼滤波的原理，我不是很清楚。
我认为“测量”是对当前帧中移动目标的检测。检测到的参数包括目标的质心位置和轮廓大小。
这些是我个人的看法。如有不妥之处，望指正。