Howtosignalprocessing
- How are facial landmarks detected?
- Which dataset is used in face recognition?
- What is 68 facial landmarks?
- What is face landmark estimation?
How are facial landmarks detected?
The best algorithms use face preprocessing coupled with face alignment to improve facial recognition. These algorithms often use multi-task cascaded convolutional networks (MTCNN) to detect faces and localize landmarks. Emotional expressions are detectable through lip, eye, and eyebrow movements.
Which dataset is used in face recognition?
The PASCAL FACE dataset is a dataset for face detection and face recognition. It has a total of 851 images which are a subset of the PASCAL VOC and has a total of 1,341 annotations. These datasets contain only a few hundreds of images and have limited variations in face appearance.
What is 68 facial landmarks?
Dlib's 68-point facial landmark detector tends to be the most popular facial landmark detector in the computer vision field due to the speed and reliability of the dlib library. However, other facial landmark detection models exist.
What is face landmark estimation?
Face landmark estimation is where we identify key points on a face, such as the tip of the nose and the center of the eye. On the left is a face that we extracted from a photograph using face detection model. On the right is what that image looks like after we use face landmark estimation to detect points on the face.
