Face recognition is one of the most innovative applications of computer vision and has gone through numerous breakthroughs in recent years. There are a plethora of real-world applications where facial detection and recognition are leveraged, such as Facebook, where it is used for image tagging. There are numerous ways to do facial detection, such as by using Haar cascade, Histogram of oriented gradients (HOG), and CNN-based algorithms. Human facial recognition is an amalgamation of two basic steps: the first is facial detection, that is, locating a human face in an image, while the other is identifying the human face.
In this recipe, we will use the image.libfacedetection package in R, which provides a convolutional neural network-based implementation for face detection, and then build a classifier/recognizer for face recognition. The steps for...
