{"id":"https://openalex.org/W4403678465","doi":"https://doi.org/10.1109/case59546.2024.10711786","title":"Investigating Low Data, Confidence Aware Image Prediction on Smooth Repetitive Videos using Gaussian Processes","display_name":"Investigating Low Data, Confidence Aware Image Prediction on Smooth Repetitive Videos using Gaussian Processes","publication_year":2024,"publication_date":"2024-08-28","ids":{"openalex":"https://openalex.org/W4403678465","doi":"https://doi.org/10.1109/case59546.2024.10711786"},"language":"en","primary_location":{"id":"doi:10.1109/case59546.2024.10711786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112963480","display_name":"Nikhil U. Shinde","orcid":null},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nikhil U. Shinde","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071963918","display_name":"Xiao Liang","orcid":"https://orcid.org/0000-0001-9127-7096"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiao Liang","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058235831","display_name":"Florian Richter","orcid":"https://orcid.org/0000-0002-7669-1923"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Florian Richter","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071321544","display_name":"Sylvia Herbert","orcid":"https://orcid.org/0000-0002-3863-8945"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sylvia Herbert","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5054598974","display_name":"Michael C. Yip","orcid":"https://orcid.org/0000-0001-9689-0172"},"institutions":[{"id":"https://openalex.org/I36258959","display_name":"University of California San Diego","ror":"https://ror.org/0168r3w48","country_code":"US","type":"education","lineage":["https://openalex.org/I36258959"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael C. Yip","raw_affiliation_strings":["University of California San Diego"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of California San Diego","institution_ids":["https://openalex.org/I36258959"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I36258959"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1845","last_page":"1852"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9668999910354614,"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"}},"topics":[{"id":"https://openalex.org/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.9668999910354614,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9646999835968018,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9538000226020813,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6638903021812439},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5756555795669556},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5699464082717896},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4862021803855896},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4356161653995514},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.42936909198760986},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4113997519016266}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6638903021812439},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5756555795669556},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5699464082717896},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4862021803855896},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4356161653995514},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42936909198760986},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4113997519016266},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/case59546.2024.10711786","is_oa":false,"landing_page_url":"https://doi.org/10.1109/case59546.2024.10711786","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE 20th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":33,"referenced_works":["https://openalex.org/W46545661","https://openalex.org/W1498436455","https://openalex.org/W1913356549","https://openalex.org/W2064675550","https://openalex.org/W2107775979","https://openalex.org/W2115579991","https://openalex.org/W2162717641","https://openalex.org/W2765906606","https://openalex.org/W2800283575","https://openalex.org/W2963669520","https://openalex.org/W2970140906","https://openalex.org/W2973966280","https://openalex.org/W3008381373","https://openalex.org/W3133294546","https://openalex.org/W3133319347","https://openalex.org/W4211049957","https://openalex.org/W4387143439","https://openalex.org/W6632008029","https://openalex.org/W6637568146","https://openalex.org/W6640963894","https://openalex.org/W6649038772","https://openalex.org/W6680657880","https://openalex.org/W6682545633","https://openalex.org/W6712884540","https://openalex.org/W6752643364","https://openalex.org/W6755634304","https://openalex.org/W6757613341","https://openalex.org/W6760827199","https://openalex.org/W6765345386","https://openalex.org/W6767408606","https://openalex.org/W6771200186","https://openalex.org/W6784227514","https://openalex.org/W7038994942"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W2779427294","https://openalex.org/W2775347418","https://openalex.org/W2625805835","https://openalex.org/W2079911747","https://openalex.org/W3116076068","https://openalex.org/W3003936178","https://openalex.org/W2145652935","https://openalex.org/W1964286703","https://openalex.org/W2169866437"],"abstract_inverted_index":{"The":[0],"ability":[1,158],"to":[2,8,54,62,82,84,120,125,141,159],"predict":[3,55],"future":[4,29,97],"states":[5,30],"is":[6],"crucial":[7],"informed":[9],"decision-making":[10],"while":[11],"interacting":[12],"with":[13,56,103],"dynamic":[14],"environments.":[15],"With":[16],"cameras":[17],"providing":[18],"a":[19,36,122,143,172],"prevalent":[20],"and":[21,136,157,192],"information-rich":[22],"sensing":[23],"modality,":[24],"the":[25,76,93,179],"problem":[26,94],"of":[27,38,78,95,99,181],"predicting":[28,96,189],"from":[31,107,195],"image":[32,101,126],"sequences":[33],"has":[34],"garnered":[35],"lot":[37],"attention.":[39],"Current":[40],"state-of-the-art":[41],"methods":[42,72],"typically":[43],"train":[44],"large":[45,79],"parametric":[46],"models":[47,59,119],"for":[48,146,153],"their":[49,68,154],"predictions.":[50,69,148],"Though":[51],"often":[52,60],"able":[53],"accuracy":[57],"these":[58,71],"fail":[61],"provide":[63],"interpretable":[64,104],"confidence":[65,105,144],"metrics":[66],"around":[67],"Additionally":[70],"are":[73,151,169],"reliant":[74],"on":[75,92,171,184],"availability":[77],"training":[80,110,163],"datasets":[81],"converge":[83],"useful":[85],"solutions.":[86],"In":[87],"this":[88,114],"paper,":[89],"we":[90,116],"focus":[91],"images":[98],"an":[100],"sequence":[102],"bounds":[106],"very":[108],"little":[109],"data.":[111],"To":[112],"approach":[113,124,183],"problem,":[115],"use":[117],"non-parametric":[118],"take":[121],"probabilistic":[123],"prediction.":[127],"We":[128,177],"generate":[129,142],"probability":[130],"distributions":[131],"over":[132],"sequentially":[133],"predicted":[134],"images,":[135],"propagate":[137],"uncertainty":[138],"through":[139],"time":[140],"metric":[145],"our":[147,182],"Gaussian":[149],"Processes":[150],"used":[152],"data":[155,164,187],"efficiency":[156],"readily":[160],"incorporate":[161],"new":[162],"online.":[165],"Our":[166],"method\u2019s":[167],"predictions":[168],"evaluated":[170],"smooth":[173],"fluid":[174],"simulation":[175],"environment.":[176],"showcase":[178],"capabilities":[180],"real":[185],"world":[186],"by":[188],"pedestrian":[190],"flows":[191],"weather":[193],"patterns":[194],"satellite":[196],"imagery.":[197]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
