Question - How does face verification work?
Answer -
Face verification is used by a lot of popular firms these days. Facebook is famous for its usage of DeepFace for its face verification needs.
There are four main things you must consider when understanding how to face verification works:
Input: Scanning an image or a group of images
Process:
- Detection of facial features
- Feature comparison and alignment
- Key pattern representation
- Final image classification
Output: Face representation, which is a result of a multilayer neural network
Training data: Involves the usage of thousands of millions of images
The implementation of face verification in Python requires special libraries such as glob, NumPy, OpenCV(cv2), and face_recognisation. Among them, OpenCV is one of the most widely used libraries for computer vision and image processing.
OpenCV is a beginner-friendly, cross-platform python library that is mainly used for real-time image and video processing applications. WithOpenCV, you can create applications used for object detection, facial recognition, and object tracking. It can also be used to extract the facial features and identify unique patterns for face verification.