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It's what I'm currently doing with a project now. Your goal is to find the smallest size of an image that a face can be detected from. You've trained an LBP to detect faces, but are receiving false positives.
You can constrain the positives by using another cascade to detect for eyes. For example, you find 5 faces in an image 1024x768. 4 are real people, while one is the cascade giving a false positive (on a wall or something).
By using the eye-detection cascade, you can feed the detected faces into the eye detector. Do this with the image(cv::Rect eyes), where image is where the webcam image is stored. If then, you watch for the size of the vector<cv::rect> where the eyes are stored, you can tell if it's successful or not. If it's a null vector, it's probably a fake face.
