Abstract: Human face recognition is a field of study in Computer Vision, and is also considered a research area of Biometrics (similar to fingerprint recognition, or iris recognition). In terms of general principles, facial recognition has a great resemblance to fingerprint recognition and iris recognition, but the difference lies in the specific extraction step of each field. While fingerprint and iris recognition has reached maturity, which is widely applicable in practice, facial recognition remains challenging and remains an interesting area of research with many. people. Compared to fingerprint and iris recognition, facial recognition has a richer data source (you can see human faces in any photo or video clip related to people online) and requires less more controlled interaction (to perform fingerprint or iris recognition, human input requires cooperation in a controlled environment).
Currently, the face recognition methods are divided into many directions according to different criteria: still image based FR (2D) recognition is the most popular, but the future will probably be. 3D (because the layout of many 2D cameras will give 3D data and give better and more reliable results), it can also be divided into two directions: doing with image data and doing with video data.
Keywords: Human faces, iris recognition, facial recognition, fingerprint recognition
| DOI: 10.17148/IJARCCE.2022.11801