CODEWITHSUNDEEP
opencv
mantithetical
mantithetical

Reputation: 1775

How does the parameter scaleFactor in detectMultiScale affect face detection?

I am trying out a slight variation of the example from http://docs.opencv.org/2.4.4-beta/doc/tutorials/introduction/desktop_java/java_dev_intro.html

    CascadeClassifier faceDetector = new CascadeClassifier("/haarcascade_frontalface_default.xml");
    Mat image = Highgui.imread(originalFile.getAbsolutePath());
    MatOfRect faceDetections = new MatOfRect();
    double w = ((double)originalCrop.getWidth());
    double h = ((double)originalCrop.getHeight());
    faceDetector.detectMultiScale(image, faceDetections, 3, 1, 
                   Objdetect.CASCADE_DO_CANNY_PRUNING , new Size(w/16, h/16), new Size(w/2, h/2));

From the API: scaleFactor – Parameter specifying how much the image size is reduced at each image scale.

Changing the scaleFactor changes what is detected. For example, for the following image: http://graphics8.nytimes.com/images/2013/04/02/world/MOSCOW/MOSCOW-articleLarge-v2.jpg

scaleFactor of 3 --> Gorbachev's face is not detected
scaleFactor of 2 --> Gorbachev's face is detected twice (one larger rectangle containing a smaller one)
scaleFactor of 1.01 ---> Gorbachev's face is detected once

How exactly does this work?

Upvotes: 4

Views: 7079

Answers (1)

mantithetical
mantithetical

Reputation: 1775

Answered over at the opencv forum:

Basically the scale factor is used to create your scale pyramid. More explanation can be found here. In short. Your model has a fixed size defined during training. This means that this size of face is detected in the image if occuring. However, by rescaling the input image, you can resize a larger face towards a smaller one, making it detectable for the algorithm. Using a small step for resizing, for example 1.05 which means you reduce size by 5 %, you increase the chance of a matching size with the model for detection is found.

Upvotes: 5

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