Learning the background model using images

asked 2019-12-28 19:25:49 -0600

papabiceps gravatar image

I have a set of images of a scene taken under slightly changing lighting conditions and objects in the scene move slightly from their positions (SET 1). I have another set of images where one or more objects in the scene are missing or misaligned (SET 2).

I want to train a background subtraction model by learning a background model using SET 1 and find the missing or misaligned objects in SET 2 using the background model. Is there a way to do this using OpenCV?

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i'm sceptic, that this idea will work.

there is no explicit seperation between train/predict functionality, so it will also learn from SET2

berak gravatar imageberak ( 2019-12-31 10:37:22 -0600 )edit

You can extract the modeled background from the OpenCV BackgroundSubtractors. https://docs.opencv.org/4.2.0/d7/df6/...

So if you feed it all of SET1, then get the background image, it won't learn.

Alternatively, set the learning rate in the apply method to 0 for the SET2 images.

Tetragramm gravatar imageTetragramm ( 2019-12-31 19:51:16 -0600 )edit
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