{"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/tertiary-eye-movement-classification-by-a","title":"Tertiary Eye Movement Classification by a Hybrid Algorithm","arxiv_id":"1904.10085","date":"2019-04-22","proceeding":null,"authors":["Samuel-Hunter Berndt","Douglas Kirkpatrick","Timothy Taviano","Oleg Komogortsev"],"abstract":"The proper classification of major eye movements, saccades, fixations, and\nsmooth pursuits, remains essential to utilizing eye-tracking data. There is\ndifficulty in separating out smooth pursuits from the other behavior types,\nparticularly from fixations. To this end, we propose a new offline algorithm,\nI-VDT-HMM, for tertiary classification of eye movements. The algorithm combines\nthe simplicity of two foundational algorithms, I-VT and I-DT, as has been\nimplemented in I-VDT, with the statistical predictive power of the Viterbi\nalgorithm. We evaluate the fitness across a dataset of eight eye movement\nrecords at eight sampling rates gathered from previous research, with a\ncomparison to the current state-of-the-art using the proposed quantitative and\nqualitative behavioral scores. The proposed algorithm achieves promising\nresults in clean high sampling frequency data and with slight modifications\ncould show similar results with lower quality data. Though, the statistical\naspect of the algorithm comes at a cost of classification time.","url_abs":"http://arxiv.org/abs/1904.10085v1","url_pdf":"http://arxiv.org/pdf/1904.10085v1.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":[{"paper_slug":"tertiary-eye-movement-classification-by-a","repo_url":"https://github.com/BerndtSam/I-VDT-HMM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}