卡尔曼跟踪 - 测量方差 [英] Kalman Tracking - Measurement variance

问题描述

我正在使用天花板安装的朝下相机进行一些跟踪移动物体的工作。我已经到了可以检测每个帧中所需对象的位置。

I'm doing some work on tracking moving objects using a ceiling mounted downward facing camera. I've got to the point where I can detect the position of the desired object in each frame.

我正在研究使用卡尔曼滤波器跟踪对象的位置和速度通过场景，我已经到达一个绊脚石。我设置了我的系统，并拥有卡尔曼滤波器除了测量方差之外的所有必需部分。

I'm looking into using a Kalman filter to track the object's position and speed through the scene and I've reached a stumbling block. I've set up my system and have all the required parts of the Kalman filter except the measurement variance.

我想为每个测量指定一个有意义的方差，以允许校正阶段以合理的方式使用新信息。我有几个措施分配给我的被检测的对象，这在理论上可以用于确定位置应该是多么准确，似乎合乎逻辑，尝试和组合他们导出一个合适的方差。

I want to be able to assign a meaningful variance to each measurement to allow the correction phase to use the new information in a sensible manner. I have several measures assigned to my detected objects which could in theory be useful in determining how accurate the position should be and it seems logical to try and combine them to derive a suitable variance.

我以正确的方式接近这一点，如果是这样，任何人都可以指向正确的方向继续？

Am I approaching this in the right manner and if so, can anyone point me in the right direction to continue?

任何帮助非常感激。

推荐答案

我认为你是对的。根据此信息：

传感器与卡尔曼滤波器融合

确定方差为100％实验。在我看来，你有你需要的一切，得到良好的方差估计。

I think you are right. According to this post:
Sensor fusioning with Kalman filter
determining the variance is 100% experimental. It seems to me you have everything you need to get good estimates of the variance.

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