traincascade - train for detecting logo

asked 2015-03-27 18:32:16 -0500

Barry gravatar image


Your problem is pretty simple, basically your training says that it can no longer improve your cascade with the current training samples and settings beyond stage 3.... ... with only 5 positive samples will never work decently.

Thanks for your reply.

My ultimate application is to detect a cereal box on a shelf among other different cereal boxes.

In the documentation, I don't remember where, I've seen discussion of training for logos. I think this is basically what I'm doing.

What I will probably do is generate 50 or so copies of the cereal box rotated and scaled slightly overlaid within a random blurry background of Mosaicy colors. My background images will consist of probably around 100 of these Mosaicy colored images.

These positive and negative images will all be the same size.

I have almost no experience with this – I have no idea if this will work.

Can someone offer some pointers? Does this seem like a good approach? How would you approach the detection of a cereal box on the shelf?

Thanks for any insights, Barry.

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The standard approach is rather via features like Sift/Surf/Orb/Freak/...

FooBar gravatar imageFooBar ( 2015-03-27 19:53:25 -0500 )edit

Thanks for the reply. I tried feature detection using car logos instead of cereal boxes. See this post:

I ended up with many feature matches. There are more matches for the desired objects, but I'm not sure how to cluster those while ignoring the undesired matches. Someone suggested cascade detection.

I've also tried template matching and had the best results with this, although I'm not sure how it would respond with very slight scaling, rotation, and skew differences.

Barry gravatar imageBarry ( 2015-03-28 13:50:43 -0500 )edit