问题描述
我想写一个的简单的跟踪程序对电影跟踪一些问题。
I'm trying to write a simple tracking routine to track some points on a movie.
基本上我有一系列的100帧长的电影，呈现出一些亮点在黑暗的背景。我有〜100-150斑点每帧，和它们上移动动画的过程。我想跟踪他们，所以我在寻找一些有效的（但可能不是overkilling执行）例程来做到这一点。
Essentially I have a series of 100-frames-long movies, showing some bright spots on dark background.I have ~100-150 spots per frame, and they move over the course of the movie. I would like to track them, so I'm looking for some efficient (but possibly not overkilling to implement) routine to do that.
这几个相关信息：
- 景点有几个（ES，5×5）的大小像素
- 动作并不大。即期一般不会从原来的位置移到超过5-10个像素。运动是一般光滑。
- 在这些景点的形一般是固定的，他们不增长或收缩，但他们变得像电影的进展并不乐观。
- 斑点不以特定的方向移动。他们可以向右移动，然后离开，然后便又
- 用户将选择周围各点的区域，然后该区域将被跟踪，所以我并不需要自动找到点。
由于视频是B / W，不过，我觉得我应该依靠brigthness。比如我以为我可以移动的周边地区，并计算与在下一帧中的各个位置上的previous帧中的区域的面积的相关性。我明白，这是一个相当幼稚的解决方案，但你觉得它可能工作？有谁知道，做到这一点的具体算法？它并不需要是超快的，只要它是正确的，我很高兴。
As the videos are b/w, I though I should rely on brigthness. For instance I thought I could move around the region and calculate the correlation of the region's area in the previous frame with that in the various positions in the next frame. I understand that this is a quite naïve solution, but do you think it may work? Does anyone know specific algorithms that do this? It doesn't need to be superfast, as long as it is accurate I'm happy.
感谢您
尼科
推荐答案
我建议皮尔逊的产品。具有模型（其可以是任何模板图像），可以测量模板的相关性的帧的任何部分。
I would suggest the Pearson's product. Having a model (which could be any template image), you can measure the correlation of the template with any section of the frame.
其结果是确定与模板1的样本的相关性的概率因子。它尤其适用于2D箱子。它具有这样的优点，以从样品绝对值是独立的，因为结果是依赖于与样品的平均值相关的协方差。
The result is a probability factor which determine the correlation of the samples with the template one. It is especially applicable to 2D cases.It has the advantage to be independent from the sample absolute value, since the result is dependent on the covariance related with the mean of the samples.
一旦检测到高的概率，你可以在原来的位置的neightboor跟踪连续帧，并选择最佳的相关系数。
Once you detect an high probability, you can track the successive frames in the neightboor of the original position, and select the best correlation factor.
但是，大小和的模板物质的转动，但是这不是因为我可以理解这种情况。您可以自定义检测任意形状，因为模板图像可以重新present任何配置。
However, the size and the rotation of the template matter, but this is not the case as I can understand. You can customize the detection with any shape since the template image could represent any configuration.
下面是一个单程算法实现，我已经使用并正常运行
Here is a single pass algorithm implementation , that I've used and works correctly.
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