Background Subtraction Using Ensembles of Classifiers with an ...

Figure 3.1. Set of Haar features being usedFigure 3.2. Illustration of equation to compute Haar valuethe value of a box is computed using Equation 3.3, which is illustrated in Figure 3.2. In theillustration, the points represent different values of the integral image. A HaarBox is any of theblack and white regions within the Haar features shown in Figure 3.1.IN(p x,y ) = IN(p x,y−1 ) + IN(p x−1,y ) − IN(p x−1,y−1 ) − I(p x,y ) (3.2)HaarBox = IN(x, y) + IN(x + width, y + height) − IN(x, y + height) + IN(x + width, y) (3.3)An example of how the value for a particular Haar feature is computed will now be shown.Suppose that Haar Feature 1 is to be computed at point x = 20, y = 20, using a 12x12 sizedwindow. First the values of the boxes that define the feature are computed. As seen in Figure3.1, one box covers the left half of the window and the other box covers the right half. For boxon the left half the boundaries of the box are: left = 14, right = 20, top = 14,bottom = 26. Forthe box on the right half the boundaries of the box are: left = 20, right = 26, top = 14,bottom= 26. Using the integral image from Equation 3.2, the value for the left box (V l ) is computedusing Equation 3.3: V l = IN(20, 26) + IN(14, 14) − IN(14, 26) − IN(20, 14). The value of the right22