Head Pose-Invariant Eyelid and Iris Tracking Method

These days, there is more demand for a camera-based gaze estimation method for new interfaces and new marketing measurement tools. Considering these applications, the system should track a new user without any operation such as calibration. It should also admit user's natural head pose changes. Previous methods, however, need a calibration procedure before execution and have less accuracy in a head moving situation. In this paper, we propose a method which tracks the user's eyelids and iris automatically and accurately. Our method is a pretreatment of gaze estimation without any calibration and head pose restraint. First of all, we track the facial feature points from an input face image and estimate its head pose, extracting the eye region image. On the eye region image, we track the eyelid shape based on an eyelid shape model generated beforehand from PCA. Finally we track the iris inside the eyelid based on the eyeball model. The eyelid and iris tracking is processed by Particle Filter. An evaluation against a database including head pose changes confirmed that the accuracy of eyelid and iris tracking was improved compared with previous methods.