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This is a Python solution, but you can port it to C++ easily.

training = cv2.imread('sample.jpg')
gray = cv2.imread('sample.jpg', cv2.CV_LOAD_IMAGE_GRAYSCALE)

val, mask = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY)

Compute the histogram:

hsv = cv2.cvtColor(training, cv2.COLOR_BGR2HSV)
h = cv2.calcHist([hsv], channels=[0,1], mask=mask, histSize=[36,50], ranges=[0,180,0,255])

Finally:

test = cv2.imread('test.jpg')
test_hsv = cv2.cvtColor(test, cv2.COLOR_BGR2HSV)
skin = cv2.calcBackProject([test_hsv], [0,1], h, ranges=[0,180,0,255], scale=1.0)