Facial recognition is a biometric solution that measures the unique characteristics of faces. To perform facial recognition, you'll need a way to uniquely represent a face.
The main idea behind any face recognition system is to break the face down into unique features, and then use those features to represent identity.
Building a robust pipeline for feature extraction is very important, as it will directly affect the performance and accuracy of our system. In 1960, Woodrow Bledsoe used a technique involving marking the coordinates of prominent features of a face. Among these features were the location of hairline, eyes, and nose.
Later, in 2005, a much robust technique was invented, Histogram of Oriented Gradients (HOG). This captured the orientation of the dense pixels in the provided image.
The most advanced technique yet, outperforming all others...
Later, in 2005, a much robust technique was invented, Histogram of Oriented Gradients (HOG). This captured the orientation of the dense pixels in the provided image.
The most advanced technique yet, outperforming all others...
