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How to define a transparent feature in Feature Descriptor?

asked 2017-09-06 02:08:45 -0600

gino0717 gravatar image

hi all, I'm following this tutorial to learning how to write some feature descriptor for svm and other machine learning tools, and it works really fine. However, I came up a question and search for some times and ask on several websites but got no answer : is there any way to descript the transparent feature?

for example, when I train the HOG model, the background always in same color, like

image description this is a hand

the background would always be the same color. It would always be classified correctly when the test data's background is simple in the HOG, for example, when our test data is in simple color background, like pure green, pure blue....

image description svm says: ok, I think this is a hand

but since the background always have some color, the svm always wants to find something in background, if the background is too different from the training data, the svm may cannot recognize it in some situtation.

image description svm says: I don't know what's this. the background is too different from your training data

As we the painter, we know that the transparency always not equal to whole white background, transparency should be transparency itself

image description is not image description

in neural network, I can collect some same foreground data with as many as possible background to get the result like " the classifier don't care about what your background is" result. but Is there way can make it like, define and train the region which is "transparency" in the data?

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answered 2017-09-06 03:00:42 -0600

That is because HOG is a gradient based approach on grayscale images, thus other colours do not influence the gradients. Machine learning is basically what you see is what you get, so if the model never saw scrambled backgrounds, then it will not know what to do with it. Providing transparacy in machine learning does not work, because we are running a pixel based evaluation....

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that is so sad

gino0717 gravatar imagegino0717 ( 2017-09-06 21:03:43 -0600 )edit

its not sad ... its just how machine learning works ... imagine a baby that has never seen cluttered backgrounds before. It will immediatly get new visual impulses and not really know what to do with it, taking a guess but from time to time failing at a task. Machine learning is identical to that.

StevenPuttemans gravatar imageStevenPuttemans ( 2017-09-07 02:18:57 -0600 )edit

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Asked: 2017-09-06 02:08:45 -0600

Seen: 152 times

Last updated: Sep 06 '17