[英]Which background substraction methods I should follow?
I have a college work which I have a short video to cut the background off (keeping only what moves in the scene) with three differente method,我有一个大学作品,我有一个短视频来用三种不同的方法剪掉背景(只保留场景中移动的东西),
So I searched and found this example from OpenCV: https://docs.opencv.org/3.4/d1/dc5/tutorial_background_subtraction.html So I guess this should be the first one所以我从 OpenCV 搜索并找到了这个例子: https : //docs.opencv.org/3.4/d1/dc5/tutorial_background_subtraction.html所以我想这应该是第一个
And this : https://learnopencv.com/simple-background-estimation-in-videos-using-opencv-c-python/ Should be the median fundus..而这个: https : //learnopencv.com/simple-background-estimation-in-videos-using-opencv-c-python/应该是眼底中位数..
Am I right?我对吗? I'm confused because the teacher did not pass us the terms in english.我很困惑,因为老师没有给我们传授英语术语。 This algorithms are right with the methods required?该算法是否与所需的方法相符? Or where can I find example of these methods?或者我在哪里可以找到这些方法的例子?
There are 2 types of background subtraction:有两种类型的背景减法:
Morphological operation based基于形态学操作
This approach assumes that background is constant or better saying that it works fine if the background is constant.这种方法假设背景是恒定的,或者更好地说,如果背景是恒定的,它就可以正常工作。 What I mean is that camera is stable.我的意思是相机是稳定的。
Note: In this approach, the biggest problem is lightening.注意:在这种方法中,最大的问题是减光。
Artificial Intelligence(AI) based基于人工智能(AI)
This method is the popular one and used widely.这种方法很流行,应用广泛。 Many meeting app in store are also using this one to change background.商店中的许多会议应用程序也在使用这个来更改背景。 This approach basically detect the target objects and mask them.这种方法基本上检测目标对象并屏蔽它们。 As an example you may have a look at the Mask-RCNN .作为一个例子,你可以看看Mask-RCNN 。 So after detecting mask of target(human, car etc.), its very easy to change background.所以在检测到目标(人、汽车等)的掩码后,很容易改变背景。 Camera movement and background changings don't affect.相机移动和背景变化不受影响。
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