Inheriting crafts work skill by augmented eye-tracking data on fixed cameras

Abstract

In aging society, traditional arts seriously face on difficulties of finding successor because the artisan skill has to be handed on through among them. This research aims to extract the gazing point from head mounted camera and visualize it on fixed cameras for skill acquisition to hand down invisible heritage. In this research, augmented eye-tracking data on fixed cameras are able to visualize craftsman's inclination of the eye movement and make advance by overlapping the images through SIFT matching and affine transform. We applied this system on Japanese traditional art skills of cutting and pasting gold leaf, which is called "KIRIKANE". From visualized images, we found that craftsman unconsciously pays attention to two specific areas on working space in the cutting phase. In the pasting phase, craftsman's gazing point does not get out of alignment from pasting line. Furthermore, the visualized images made the learners of the "KIRIKANE" easier to understand craftsman's skill.