{"id":"https://openalex.org/W7133349057","doi":"https://doi.org/10.1109/ijcb65343.2025.11411463","title":"From Features to Embeddings: Extending the Temporal-Persistence Principle to Deep-Learning Eye-movement Biometric","display_name":"From Features to Embeddings: Extending the Temporal-Persistence Principle to Deep-Learning Eye-movement Biometric","publication_year":2025,"publication_date":"2025-09-08","ids":{"openalex":"https://openalex.org/W7133349057","doi":"https://doi.org/10.1109/ijcb65343.2025.11411463"},"language":null,"primary_location":{"id":"doi:10.1109/ijcb65343.2025.11411463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5033757145","display_name":"Mehedi Hasan Raju","orcid":"https://orcid.org/0000-0002-1144-6118"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mehedi Hasan Raju","raw_affiliation_strings":["Texas State University,San Marcos,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Texas State University,San Marcos,Texas,USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5128027601","display_name":"Lee Friedman","orcid":null},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lee Friedman","raw_affiliation_strings":["Texas State University,San Marcos,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Texas State University,San Marcos,Texas,USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062654909","display_name":"Dillon Lohr","orcid":"https://orcid.org/0000-0002-8088-9270"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dillon Lohr","raw_affiliation_strings":["Texas State University,San Marcos,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Texas State University,San Marcos,Texas,USA","institution_ids":["https://openalex.org/I13511017"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035152487","display_name":"Oleg V. Komogortsev","orcid":"https://orcid.org/0000-0001-7890-8842"},"institutions":[{"id":"https://openalex.org/I13511017","display_name":"Texas State University","ror":"https://ror.org/05h9q1g27","country_code":"US","type":"education","lineage":["https://openalex.org/I13511017"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Oleg V. Komogortsev","raw_affiliation_strings":["Texas State University,San Marcos,Texas,USA"],"affiliations":[{"raw_affiliation_string":"Texas State University,San Marcos,Texas,USA","institution_ids":["https://openalex.org/I13511017"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033757145"],"corresponding_institution_ids":["https://openalex.org/I13511017"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.81489818,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"11"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.906499981880188,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.906499981880188,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.01979999989271164,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11094","display_name":"Face Recognition and Perception","score":0.008799999952316284,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.8712000250816345},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6164000034332275},{"id":"https://openalex.org/keywords/gaze","display_name":"Gaze","score":0.5827000141143799},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5415999889373779},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.41280001401901245},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4081999957561493},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.40540000796318054},{"id":"https://openalex.org/keywords/signal","display_name":"SIGNAL (programming language)","score":0.30329999327659607}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8712000250816345},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6887000203132629},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6517999768257141},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6164000034332275},{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.5827000141143799},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5415999889373779},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4081999957561493},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3140000104904175},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.31349998712539673},{"id":"https://openalex.org/C2779843651","wikidata":"https://www.wikidata.org/wiki/Q7390335","display_name":"SIGNAL (programming language)","level":2,"score":0.30329999327659607},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.2913999855518341},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.27630001306533813},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.2709999978542328},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C2781009140","wikidata":"https://www.wikidata.org/wiki/Q7170389","display_name":"Persistence (discontinuity)","level":2,"score":0.26080000400543213},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.25270000100135803}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcb65343.2025.11411463","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb65343.2025.11411463","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.5895719528198242,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W607462674","https://openalex.org/W1554675373","https://openalex.org/W1989000482","https://openalex.org/W2023011901","https://openalex.org/W2028158865","https://openalex.org/W2068521782","https://openalex.org/W2080000582","https://openalex.org/W2093923187","https://openalex.org/W2094773601","https://openalex.org/W2109606373","https://openalex.org/W2122814955","https://openalex.org/W2135931512","https://openalex.org/W2181315643","https://openalex.org/W2187920722","https://openalex.org/W2228006265","https://openalex.org/W2288826045","https://openalex.org/W2313879993","https://openalex.org/W2335129493","https://openalex.org/W2405531384","https://openalex.org/W2519344800","https://openalex.org/W2537284801","https://openalex.org/W2606828393","https://openalex.org/W2617428610","https://openalex.org/W2772180746","https://openalex.org/W2784260270","https://openalex.org/W2795516647","https://openalex.org/W2803949348","https://openalex.org/W2908076704","https://openalex.org/W2955871884","https://openalex.org/W2963446712","https://openalex.org/W2963587345","https://openalex.org/W2964271799","https://openalex.org/W2994517173","https://openalex.org/W3023011947","https://openalex.org/W3025840242","https://openalex.org/W3031452559","https://openalex.org/W3032172280","https://openalex.org/W3043980307","https://openalex.org/W3049707285","https://openalex.org/W3091362518","https://openalex.org/W3119689663","https://openalex.org/W3127185310","https://openalex.org/W3128446111","https://openalex.org/W3153158691","https://openalex.org/W3179188416","https://openalex.org/W3203543114","https://openalex.org/W3204795127","https://openalex.org/W4212786542","https://openalex.org/W4281719442","https://openalex.org/W4292968994","https://openalex.org/W4399199487","https://openalex.org/W4399202815","https://openalex.org/W4401019736","https://openalex.org/W4404238834","https://openalex.org/W4411996838"],"related_works":[],"abstract_inverted_index":{"Eye":[0],"movement":[1,61],"biometric":[2,20,62,84,106,156],"has":[3],"recently":[4],"reached":[5],"a":[6,11,26,55,65,99,141],"meaningful":[7],"performance":[8,21,85,103],"threshold":[9],"within":[10],"gaze":[12],"estimation":[13],"pipeline.":[14],"Prior":[15],"research":[16],"claimed":[17],"that":[18,92,131,146,160],"good":[19],"can":[22],"be":[23],"achieved":[24],"from":[25],"relatively":[27],"large":[28],"set":[29],"of":[30,42,54,76,78,97,102,128,133,148,154],"weakly":[31,165],"intercorrelated":[32],"features":[33],"with":[34],"high":[35],"temporal":[36,93,126,138],"persistence":[37,127],"(indexed":[38],"by":[39,95],"the":[40,52,74,112,125],"measurement":[41,75,96,147],"reliability).":[43],"In":[44],"this":[45,49],"study,":[46],"we":[47,71,144],"revisit":[48],"hypothesis":[50],"in":[51,86,104],"context":[53],"modern":[56],"deep":[57],"learning":[58],"(DL)-based":[59],"eye":[60],"system,":[63],"using":[64],"publicly":[66],"available":[67],"eye-movement":[68],"dataset.":[69],"Specifically,":[70],"investigate":[72],"whether":[73],"reliability":[77,149],"learned":[79],"embeddings":[80,162],"continues":[81],"to":[82],"predict":[83],"DL-based":[87,105,113,155],"biometrics.":[88],"Our":[89],"results":[90],"confirm":[91],"persistence\u2014quantified":[94],"reliability\u2014is":[98],"significant":[100],"predictor":[101,153],"systems,":[107],"extending":[108],"prior":[109],"findings":[110],"into":[111],"biometric.":[114],"We":[115],"also":[116,159],"examine":[117],"how":[118],"manipulating":[119],"eye-tracking":[120],"signal":[121],"quality":[122],"descriptors":[123],"impacts":[124],"embeddings,":[129],"finding":[130],"degradation":[132],"any":[134],"kind":[135],"undermines":[136],"their":[137],"persistence.":[139],"As":[140],"general":[142],"matter,":[143],"found":[145],"is":[150],"an":[151],"important":[152],"performance,":[157],"and":[158],"DL-learned":[161],"are":[163],"generally":[164],"intercorrelated.":[166]},"counts_by_year":[],"updated_date":"2026-03-05T07:30:30.508283","created_date":"2026-03-04T00:00:00"}
