A Novel Quality Assessment Method for Eye Movement Authentication

Eye movement authentication has been paid attention to realize both high usability and security especially counterfeit biometric modality. Although previous researches took care for obtaining the eye movement information correctly to eliminate the noisy data, they did not focus on the quality on the captured data. In this paper, we propose the quality assessment method on eye movement authentication. Our experiment using competition data shows the peak velocity of eyeballs has the relationship with the obtained genuine similarity scores.