Object Detection - Haar Cascade / LBP Cascade - Simplest Example - Training Data

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I would like to start using the Haar/LBP Cascade Classifier.

I would like to start at the most basic level, with the most simplest example. You can compare it to what would be a ‘Hello World’ example in programming language demonstration/learning.

I have attached a link to a .ZIP file package that contains an image of a Square (with a 1-pixel white border, so that it contains ‘some’ background, if needed). I have included a coloured version and a greyscale version (I expect the greyscale version would be more appropriate for the simplest of demonstrations, But I included the colour one also, incase anything has to be done differently (in comparision) with a simple Coloured version).

Because I like to see the most basic demonstration. I wish to see the cascade classifier detect the square object, in test data that is the exact image that was provided during training (or at least 1 of them, if there has to be sevea), i.e using the the attached image as the test example also.

Can someone generate using image editing/manipulation, (or maybe opencv_creaatsamples.exe program, (less preferred)). the training data image files (.PNG file format, to avoid JPG compression artifacts being included in the training data), and also the .VECtor training file. (Also any command-line swiches that were used for all applications involved, in both the image geneartion and the training). (The training Images can be same size as the attached image)

Note: I am focusing on the bare minimum, therefore I mean;

  • The LEAST amount of training images
  • The LEAST Type of variations in the training images
  • The LEAST Amount of a particular variation in the training images
  • The SIMPLEST training options
  • Say 24x24 pixel (as in tutorial), or maybe 20x20 pixel (as used in research paper) .VECtor file dimensions ( ?)
  • (Anything else, that I have not mentioned)

Also included, are a few other basic shapes in addition to the square (to see how they handle in comparison).

Also, to provide negative training data that is also Basic, there are 2 large background images 2000x2000 pixels, that with a 24x24 window size will give 6944 background/negative samples, each. The images as also basic; Noise (Fine), Clouds.

Training Images: http://www.dropbox.com/s/6vvsmt7old4wt0u/Object_Detection_%28Basic%29.zip?dl=0
(Allows web-browser viweing of contents, without downloading)

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your training images is rubbish.
if you want making an online meeting about your questions… i can try to answer your questions.