Face recognition is a powerful application of artificial intelligence and deep learning that enables systems to identify individuals from images or video. It works by analyzing unique facial features using deep neural networks.
The process begins with face detection, where models such as MTCNN locate faces within an image. Once detected, the face is aligned and normalized to reduce the effects of lighting, pose, and orientation differences.
Next, Convolutional Neural Networks (CNNs) extract key facial features and convert them into numerical representations known as feature vectors or embeddings. Popular models like FaceNet and VGGFace are commonly used for this purpose.
Finally, these features are compared with stored facial data to identify or verify a person. This is done using classification methods such as Softmax or similarity-based algorithms like Support Vector Machines (SVM).
Face recognition is widely used in security systems, retail analytics, and social media. However, its use also raises privacy and ethical concerns, leading to ongoing discussions about responsible deployment and regulation.
