Face Recognition Thesis 2012

Face Recognition Thesis 2012-40
Therefore, face recognition in uncontrolled environments is much more challenging than in controlled conditions.Moreover, many real world applications require good recognition performance in uncontrolled environments.It actually attempts to establish whose face it is.

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Banks, retail stores, stadiums, airports and other facilities use facial recognition to reduce crime and prevent violence.

So in short, while all facial recognition systems use face detection, not all face detection systems have a facial recognition component.

While facial recognition isn’t 100% accurate, it can very accurately determine when there is a strong chance that an person’s face matches someone in the database.

There are lots of applications of face recognition.

While the process is somewhat complex, face detection algorithms often begin by searching for human eyes.

Eyes constitute what is known as a valley region and are one of the easiest features to detect.

Once eyes are detected, the algorithm might then attempt to detect facial regions including eyebrows, the mouth, nose, nostrils and the iris.

Once the algorithm surmises that it has detected a facial region, it can then apply additional tests to validate whether it has, in fact, detected a face.

Face recognition is already being used to unlock phones and specific applications.

Face recognition is also used for biometric surveillance.

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