From the course: Deep Learning: Face Recognition
Join today to access over 22,600 courses taught by industry experts or purchase this course individually.
Posing faces based on face landmarks - Python Tutorial
From the course: Deep Learning: Face Recognition
Posing faces based on face landmarks
- [Voiceover] Now that we have the ability to detect face landmarks, we can use them to make sure all of our face images are aligned. Face alignment is where we adjust each face image so that key facial features like the eyes, nose, and mouth line up with a predefined template. Here's an example of face alignment. On the left is a face that was extracted directly from a real photo. Notice how the left side of the head is turned away from the camera and how the face is slightly tilted down. On the right is the aligned version of the face. We've adjusted the image so that the eyes and bottom of the nose are as close to the center as we can get them without causing too much distortion. So, why do we need to align our face images? We want our face recognition system to work even if the person isn't looking directly into the camera. When we take pictures in the real world, a person's head will usually be rotated and not looking directly at the camera. If we don't correct for this head…
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.