1. A method comprising: capturing, by a camera of a mobile computing device, an image; generating, by the mobile computing device, a facial detection confidence score based at least in part on a likelihood that a representation of at least a portion of a face is included in the image; generating, by the mobile computing device, a facial landmark detection confidence score based at least in part on a likelihood that representations of facial landmarks are accurately identified in the image; generating, by the mobile computing device, a geometric consistency score based at least in part on a difference between a point of intersection between a nose base and a line segment that passes through each eye and a midpoint of the line segment in the image; generating, by the mobile computing device, an image quality score based at least in part on a combination of the facial detection confidence score, the facial landmark detection confidence score, and the geometric consistency score; and classifying, by the mobile computing device, a quality of the image based at least in part on the image quality score.
18. The method of claim 1 , wherein the image is classified as a good quality image, the method further comprising: determining that an absolute value amount of yaw of the face in the image is greater than a threshold amount of yaw; and reclassifying the image as a poor quality image.