EPS: Robust Pupil Edge Points Selection with Haar Feature and Morphological Pixel Patterns

Abstract

Pupil parameters are the essential foundation for many applications, such as cognitive science and human–machine interaction. Existing approaches are still affected by various challenges. We propose a novel pupil detection pipeline (known as Edge Points Selector “EPS”) which is suitable even for partial occlusion, lighting, and specular reflection. EPS consists of pupil area detection, edge selection, and ellipse fitting. For the first time, we find the suitable Haar-like feature of 2D-pupil and a new pupil edge feature in the local pupil area, and integrate them into the proposed pipeline. EPS was compared with two state-of-art methods on 130[Formula: see text]856 images in this work. Within an error threshold of 5 pixels, our method outperforms the comparison algorithms by 33.8% and 19.4%, respectively, on overage.