This paper describes a sophisticated method to track irises in a monocular video sequence with a particle filter that uses a newly proposed Iris-Eyelid separability filter (IESF). In order to reduce the influence of eyelids and to cope with the variance of the appearance of eyes of different people, we propose an Iris-Eyelid separability filter (IESF), and use it to estimate the likelihood of hypotheses in the particle filter. We confirmed that our method has the ability of tracking various eyes for different people whose head motion including translation, rotation and zoom, even when people are wearing glasses. Through the comparative experiments of the IESF and the conventional circular separability filter (CCSF), we confirmed that our iris tracking algorithm is more robustly. © 2013 The Authors.
Chen, Q., Mastumoto, K., & Wu, H. (2013). Iris-eyelid separability filter for irises tracking. In Procedia Computer Science (Vol. 22, pp. 1029–1037). Elsevier B.V. https://doi.org/10.1016/j.procs.2013.09.188