Face Algorithms

Face

face detection $\Rightarrow$ face alignment (marklands)$\to$ face embedding $\to$ face identification

Face Quality Assessment

A binary classification to judge the picture quality is good or not as a face in quality. consider the reduction of computation and increase of reliability
face detection $\to$ face alignment $\to$ quality assessment

sub-measurement

• symmetry: to make sure the pose of face satisfied. estimate by histogram intersection distance of left and right of facial local features
• head rotation/pose: measure by center of face and center of picture
• sharpness: to estimate the affect of motion blur. estimate by Laplace operator
• illumination: estimate by the length R of available range of gray intensities excluding 5% of the darkest and brightest pixels
• face size: estimate by size of bounding box
• presence of skin pixels:
• openness of eyes and red eyes:

reference

https://blog.csdn.net/u013082989/article/details/83537370