Improved pupil center localization method for eye-gaze tracking-based human-device interaction

This paper presents an improved pupil center (PC) localization method for eye-gaze tracking. In the proposed method, an input infrared eye image is repeatedly binarized with a finite number of different thresholds to produce a stack of binary images. Among all the blobs, which are groups of connected binary pixels in the binary image stack, we find a blob whose shape is the most similar to pupil, in terms of the size, the aspect ratio, the moments, and the circularity. Consequently, the centroid of the final resultant blob is regarded as the PC location. Experimental results show that the proposed method outperforms conventional ones.