使用卡尔曼滤波跟踪移动球的问题 [英] Question on tracking a moving ball using Kalman filter
问题描述
我想学习使用卡尔曼滤波器跟踪一个移动的球。虽然有很多教程可用，但我仍然有一些问题。
I want to learn to track a moving ball using Kalman filter. Although many tutorial are available, I still have some questions.
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如果我们可以在视频序列的每一帧中提取球，我们将知道球的位置。那么，为什么我们需要使用卡尔曼fiter呢？
If we can extract the ball in each frame of the video sequence, we will know the position of the ball. Then, why do we need to use Kalman fiter anymore? What is the job of Kalman filter here?
Kalman filter: x(k+1) = A.x(k) + B.u(k) + noise
y(k) = C.x(k) + noise
那么，我们如何定义A，B，C？假设我们要跟踪移动的球？
Then, how do we define A, B, C ? suppose we want to track the moving ball?
3。如果我们知道先前状态x（k-1）和当前状态y（k）的测量，则可以计算估计状态。在跟踪移动球的情况下，测量是什么？
3 . If we know the previous state x(k-1) and the measurement of the current state y(k), we can compute the estimated state. What is the "measurement" in case of tracking the moving ball?
推荐答案
你的场景。
（1）
假设你来到另一个球进入现场的点。所以你需要找到一个方法来识别每个球。
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.
您的跟踪方法（即卡尔曼滤波器）将会使您的跟踪方法然后根据球在之前移动的方式继续其在估计轨迹上的移动。
Your tracking method (i.e. Kalman filter) will then continue its movement on the estimated trajectory, based on how the ball has moved before.
因此，如果你只想知道每个帧中的球在哪里， t需要跟踪方法，但如果你想要识别和跟踪一个球，你需要一个跟踪器，即卡尔曼滤波器或多对象跟踪我喜欢粒子滤波器（http://en.wikipedia.org / wiki / Particle_Filter）。
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）
你现在在这里，因为我现在不太深入卡尔曼滤波器。
但基本上A应该是从步骤x（t-1）到x（t）的过渡矩阵，B应该是参考模型。
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）
(3)
测量将是您在图像上测量的位置。基本上你的球的中点。您将使用此度量来更正估计路径。因此，基本上你可以比较球应该在当前时间步（取决于它的以前的运动）的位置与它的实际位置。
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.
我希望有助于...如果不是，继续问...
I hope that helps... if not, keep asking...
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