{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/115430"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/115430","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Improving 3D human pose estimation in-the-wild","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","abstract_has_math":false,"creators":["Gonzalez, Victor"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Forsyth, David A"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-05","date_published":"2022-05","updated_at":"2026-07-22T22:24:54Z","subjects":["human pose estimation","occlusion"],"languages":["en","eng"],"rights":["Copyright 2022 Victor Gonzalez"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/115430","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Forsyth, David A"]},{"key":"dc:creator","label":"Author","values":["Gonzalez, Victor"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-05","2022-04-25"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["human pose estimation","occlusion"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2022 Victor Gonzalez"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/115430"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","The student, Victor Gonzalez, accepted the attached license on 2022-04-21 at 16:25.","The student, Victor Gonzalez, submitted this Thesis for approval on 2022-04-21 at 16:31.","This Thesis was approved for publication on 2022-04-25 at 15:25.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17892 on 2022-11-11 at 13:42:52","There has been some suspicion that 3D human pose estimation produces significantly worse results on in-the-wild images than on lab images. Confirming this suspicion is difficult, because it is hard to get 3D ground truth for in-the-wild images without measurement equipment significantly affecting the imagery. This thesis (a) demonstrates the suspicions are correct; (b) shows the effect is, at least in part, due to reconstructions not plausible (that is, \"like\" human poses); (c) explores simple augmentation can improve performance in situations with occlusion and (d) shows that natural methods to produce reconstructions that are plausible produce measurable improvements for in-the-wild reconstruction. Forcing methods to produce reconstructions that are plausible produces no major improvement on Human3.6M validation data; but this is because error on Human3.6M validation data is a poor predictor of error on in-the-wild data. This thesis shows that a registration error measure applied to reconstructions from multiple view data is a good predictor of ground truth error. Our registration error confirms that various procedures to enforce plausible reconstructions make notable improvements on in-the-wild error consistently across a number of distinct multiple view human action datasets."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Improving 3D human pose estimation in-the-wild"]}]}],"canonical_facts":{"dc:contributor":["Forsyth, David A"],"dc:creator":["Gonzalez, Victor"],"dc:date":["2022-05","2022-04-25"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-11 without embargo terms","The student, Victor Gonzalez, accepted the attached license on 2022-04-21 at 16:25.","The student, Victor Gonzalez, submitted this Thesis for approval on 2022-04-21 at 16:31.","This Thesis was approved for publication on 2022-04-25 at 15:25.","DSpace SAF Submission Ingestion Package generated from Vireo submission #17892 on 2022-11-11 at 13:42:52","There has been some suspicion that 3D human pose estimation produces significantly worse results on in-the-wild images than on lab images. Confirming this suspicion is difficult, because it is hard to get 3D ground truth for in-the-wild images without measurement equipment significantly affecting the imagery. This thesis (a) demonstrates the suspicions are correct; (b) shows the effect is, at least in part, due to reconstructions not plausible (that is, \"like\" human poses); (c) explores simple augmentation can improve performance in situations with occlusion and (d) shows that natural methods to produce reconstructions that are plausible produce measurable improvements for in-the-wild reconstruction. Forcing methods to produce reconstructions that are plausible produces no major improvement on Human3.6M validation data; but this is because error on Human3.6M validation data is a poor predictor of error on in-the-wild data. This thesis shows that a registration error measure applied to reconstructions from multiple view data is a good predictor of ground truth error. Our registration error confirms that various procedures to enforce plausible reconstructions make notable improvements on in-the-wild error consistently across a number of distinct multiple view human action datasets."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/115430"],"dc:language":["en","eng"],"dc:rights":["Copyright 2022 Victor Gonzalez"],"dc:subject":["human pose estimation","occlusion"],"dc:title":["Improving 3D human pose estimation in-the-wild"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:54Z"}