An Improved Eye Auxiliary Line Considering Boundary Margin, Iris, and Pupil for Portrait Drawing Learning Assistance System

Portrait drawing is effective in cultivating artistic skills and visual understanding for a lot of people. Since drawing facial features with proper proportions, structures, and spatial relationships is hard for novices with no professional guidance, we developed the Portrait-Drawing Learning Assistance System, which offers auxiliary lines to assist in the drawing of portraits by acting as references; these auxiliary lines are extracted by applying OpenPose and OpenCV to a facial image. The drawing exactness assessment method using the Localized Normalized Cross-Correlation algorithm is also implemented to evaluate drawing accuracy. Unfortunately, previous experiments involving the use of the Portrait-Drawing Learning Assistance System by novices found that Localized Normalized Cross-Correlation scores for eyes are relatively low compared with others because of two drawbacks: (1) eye boundaries are often blurred by eyelids and eyelashes, which can make eyes bigger, and (2) the iris and pupil are not considered in auxiliary lines. In this paper, we propose an improved eye auxiliary line for the Portrait-Drawing Learning Assistance System to address these concerns. For the first drawback, we shift the lines for eye boundaries outside and add hatching (a series of short line segments) to them. For the second one, we expand region of interest of an eye and apply the Canny edge detector to capture its iris and pupil. In a preliminary within-subject evaluation, eight graduate students at Okayama University used the previous and proposed eye auxiliary lines in Procreate on an iPad. The average localized NCC scores increased for both eye regions under the tested conditions. These results suggest that the proposed auxiliary line may improve immediate eye-region reproduction accuracy; however, they do not constitute definitive validation of drawing-skill learning.