opencv face-detection in java : conception steps

Question

I'm working on face-detection project via webcam using opencv
In this approach (viola-jones) to detecting object in images combines four key concepts :

1-Simple rectangular features called haar features ( i can find this one in haarcascade_frontalface_alt.xml file).

2- An integral Image for raped feature detection.

3- The AdaBoost machine-learning method.

4-A cascaded classifier to combine many features efficiently.

my questions are:

-does haarcascade_frontalface_alt.xml contains the cascaded classifier also with the haar feature?

-how can i add the integral image and AdaBoost in my project and how to use it??or is it already done automatically??

Answer 1

it seems, you've read a lot of papers and pondered ideas, but have not found the opencv implementation ;)

using it is actually quite easy:

// setup a  cascade classifier:
CascadeClassifier cascade;

// load a pretrained cascadefile(and PLEASE CHECK!):
bool ok = cascade.load("haarcascade_frontalface_alt.xml");
if ( ! ok ) 
{
    ...
}


// later, search for stuff in your img:
Mat gray; // uchar grayscale!
vector<Rect> faces; // the result vec

cascade.detectMultiScale( gray, faces, 1.1, 3, 
    CV_HAAR_FIND_BIGGEST_OBJECT | CV_HAAR_DO_ROUGH_SEARCH  ,
    cv::Size(20, 20) );

for ( size_t i=0; i<faces.size(); i++ )
{
// gray( faces[i] ); is the img portion that contains the detected object
}