Face recognition is the ability to look at the digital image of a human and recognize the person just by looking at the face.
Overview:
Face recognition is used for everything from automatically tagging pictures to unlocking cell phones. And with recent advancements in deep learning, the accuracy of face recognition has improved. This course is designed to learn how to develop a face recognition system that can detect faces in images, identify the faces, and even modify faces with "digital makeup" like you've experienced in popular mobile apps. The other outcomes of this course are to discover tools you can leverage for face recognition, see how a machine learning model can be trained to analyze images and identify facial landmarks, learn the steps involved in coding facial feature detection, representing a face as a set of measurements, and encoding faces. Additionally, learn how to repurpose and adjust pre-existing systems.
Learning objectives
- Detecting faces in images
- Analyzing a histogram of oriented gradients (HOG)
- Identifying faces in images
- Locating facial features in images
- Coding for face detection
- Finding lookalikes using face detection
- Generating face encoding automatically