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Haar Detection

OS Support:

Windows All


Publisher Old version


February 18 2011


Haar Detection


Viola and Jones used 160 000 rectangular features, the cascade of classifiers is large. In my version I prefer manually only 115 rectangular features that closly mimic eigenfaces PCA basis developed. I also have artificial neural networks (ANN) as classifiers in a cascade. So my task to develop the code library and investigate whether they lead a very small subset of the features in a robust object recognition with non-linear clasifiers is. For the object I used face detection problem, thanks there are great face databases CBCL or CMU to solve the problem.

To start with the executable file, just click on the ENUM key and select capture device, then click Init AI download cascade of classifiers ANN and press Start to initiate capture and face detection. You can change with separation control. At the bottom status static proof fps are displayed.

A precautionary measure, in comparison to my eigenfaces face detection lib, there you can get each individual rectangle and histogram it compensated before further processing, you can not use the same trick with built-in image.

Only adaptive histogram will work for the entire image before computing integral version. So the presented classifiers might be not so good low light conditions as eigenfaces code. So make sure you have your face lights up enogth over.

The hair Detection application was designed to test a small tool that allows ultra-fast object recognition.

Hair detection requirements:

  • Recorder

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    Haar Detection

    Size : 121 KB