{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/a-score-level-fusion-method-for-eye-movement","title":"A Score-level Fusion Method for Eye Movement Biometrics","arxiv_id":"1601.03333","date":"2016-01-13","proceeding":null,"authors":["Anjith George","Aurobinda Routray"],"abstract":"This paper proposes a novel framework for the use of eye movement patterns\nfor biometric applications. Eye movements contain abundant information about\ncognitive brain functions, neural pathways, etc. In the proposed method, eye\nmovement data is classified into fixations and saccades. Features extracted\nfrom fixations and saccades are used by a Gaussian Radial Basis Function\nNetwork (GRBFN) based method for biometric authentication. A score fusion\napproach is adopted to classify the data in the output layer. In the evaluation\nstage, the algorithm has been tested using two types of stimuli: random dot\nfollowing on a screen and text reading. The results indicate the strength of\neye movement pattern as a biometric modality. The algorithm has been evaluated\non BioEye 2015 database and found to outperform all the other methods. Eye\nmovements are generated by a complex oculomotor plant which is very hard to\nspoof by mechanical replicas. Use of eye movement dynamics along with iris\nrecognition technology may lead to a robust counterfeit-resistant person\nidentification system.","url_abs":"http://arxiv.org/abs/1601.03333v1","url_pdf":"http://arxiv.org/pdf/1601.03333v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[],"tasks":[{"task_slug":"iris-recognition","task_name":"Iris Recognition"},{"task_slug":"person-identification","task_name":"Person Identification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/person-identification-on-bioeye","task":"Person Identification","dataset":"BioEye","model":"RBFN","rank_in_archive_order":1,"of":1,"metrics":{"R1":"98.69"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}