Ongoing Challenges Automatic Face Recognition

Theoretical Difficulties in Automatic Face Recognition Extensive research has focused on the development of computer algorithms and advances in automatic face recognition have resulted in the development of systems that operate with high performance in a controlled environment. Although the computer AFR system does not necessarily have to imitate the face recognition process, people compete with the capabilities of computer algorithms when recognizing a well-known face, even in very poor situations.

Sometimes it is challenging to name your face, but humans are good at recognizing faces in general. On the other hand, computers often find that it is difficult to classify faces as faces. In fact, the main challenge facing face recognition is because the face shape and size are different. In addition, you can change both lighting conditions and head direction, making the challenge more difficult. Infants also tend to like facial images of meaningless images, indicating that the ability to recognize faces is at least partially hardwired. Neuroimaging studies show that face recognition depends on the activity of specific areas of the right hemisphere of the right brain and adults that damage these areas lose face recognition technology.

In recent years, research related to the field of face recognition has gained more and more attention, and it is becoming increasingly popular among researchers in the field of computer vision. Many studies are in progress in the field of face recognition. Face recognition is being studied not only by researchers of computer vision but also by psychologists and neuroscientists. In addition, the area of ​​face recognition includes entertainment (human computer interaction), smart card (national ID card or immigrant), information security (desktop login), and police and surveillance (CCTV control).