Abstract: Techniques for automated facial measurement are provided. A set of images that satisfy orientation criteria is identified, comprising, for each image in the set of images, determining an orientation of a face of a user based on a set of coordinate locations for a set of facial landmarks, where at least one image is discarded for failing to satisfy the orientation criteria. A reference distance on the face is estimated based on a first image, where the reference distance indicates a measurement of at least one of the set of facial landmarks. A nose depth of the user is estimated based on a second image based at least in part on the reference distance, and a facial mask is selected for the user based at least in part on the nose depth.

Abstract: Techniques for automated facial measurement are provided. A set of coordinates for a set of landmarks on a face of a user are extracted by processing an image using a machine learning model. An orientation of the face of the user is determined. It is determined that impedance conditions are not present in the images, and a reference distance on the face of the user is estimated based on the image, where the image depicts the user facing towards the imaging sensor. A nose depth of the user is estimated based on a second image based at least in part on the reference distance, where the second image depicts the user facing at an angle relative to the imaging sensor. A facial mask is selected for the user based on the nose depth.

Abstract: Techniques for automated facial measurement are provided. A set of coordinate locations for a set of facial landmarks on a face of a user are extracted by processing a first image using one or more landmark-detection machine learning models. An orientation of the face of the user is determined. It is determined that impedance conditions are not present in the set of images, and a reference distance on the face of the user is estimated based on the first image, where the first image depicts the user facing towards the imaging sensor. A nose depth of the user is estimated based on a second image of the set of images based at least in part on the reference distance, where the second image depicts the user facing at an angle relative to the imaging sensor. A facial mask is selected for the user based on the nose depth.