Face Recognition
Face recognition mainly involves the following stages:
- Pre-processing the images: Generally, when we work with unstructured data such as images, we are working with raw data. In the pre-processing step, we aim to improve the quality of the raw data either by removing any irregularities, such as distortions, non-alignments, and noise, or by enhancing some features using geometric transformation, such as zooming in, zooming out, translation, and rotation.
- Face detection: In this step, we aim to detect all the faces present in each image and store the faces with correct labels.
- Training (creating the face recognition model): In the training step, we take the images and their corresponding labels and feed them into a parametric algorithm that learns how to recognize a face. As a result, we get a trained parametric model that eventually helps us to recognize faces. The trained model contains some characteristic features corresponding to each unique label...
