{"id":{"repo_id":"sheffield-hallam","oai_identifier":"oai:shura.shu.ac.uk:10896"},"canonical_url":"https://search.dev.ndltd.org/etd/sheffield-hallam/oai:shura.shu.ac.uk:10896","repository":{"repo_id":"sheffield-hallam","name":"Sheffield Hallam University","base_url":"https://shura.shu.ac.uk/cgi/oai2"},"display":{"title":"Automated tracking of swimmers in the clean swimming phase of a race","abstract":"The current advice for a sports analyst when filming a large performance area is to use multiple fixed cameras or a single panning one. Neither of these options is ideal: multiple cameras must be positioned, have their shutters synchronised and their footage combined for analysis; a panning camera makes it difficult to determine an athlete’s movement relative to an external frame of reference. The aim of this study was to establish a process that enabled the confident, accurate and precise use of a wide field of view for measuring distance and speed in large performance areas. Swimming was used as an example sport as it had a large performance area, which measured 50 m by 25 m. A process for determining the accuracy and precision with which distance and speed could be reconstructed from a wide field of view was developed. A nonlinear calibration procedure was used to account for radial distortion. The Root Mean Square Error (RMSE) of reconstructed distances for a wide field of view was 16 x 10-3 m. This compared favourably with a three camera system reported in the literature, which had an RMSE of 46 x 10-3 m. In addition, it was shown that a wide field of view could be used to identify a 1% enhancement in speed when it was measured over 10 m or more. A wide field of view was used to capture video footage of a swimming competition. This was used to track swimmers using two methods: manual and automated. The two methods showed good agreement for mean speed, but the automated one had higher variability in instantaneous speed than did the manual.","abstract_html":"The current advice for a sports analyst when filming a large performance area is to use multiple fixed cameras or a single panning one. Neither of these options is ideal: multiple cameras must be positioned, have their shutters synchronised and their footage combined for analysis; a panning camera makes it difficult to determine an athlete’s movement relative to an external frame of reference. The aim of this study was to establish a process that enabled the confident, accurate and precise use of a wide field of view for measuring distance and speed in large performance areas. Swimming was used as an example sport as it had a large performance area, which measured 50 m by 25 m. A process for determining the accuracy and precision with which distance and speed could be reconstructed from a wide field of view was developed. A nonlinear calibration procedure was used to account for radial distortion. The Root Mean Square Error (RMSE) of reconstructed distances for a wide field of view was 16 x 10-3 m. This compared favourably with a three camera system reported in the literature, which had an RMSE of 46 x 10-3 m. In addition, it was shown that a wide field of view could be used to identify a 1% enhancement in speed when it was measured over 10 m or more. A wide field of view was used to capture video footage of a swimming competition. This was used to track swimmers using two methods: manual and automated. The two methods showed good agreement for mean speed, but the automated one had higher variability in instantaneous speed than did the manual.","abstract_has_math":false,"creators":["Hudson, Christopher"],"institution":"Sheffield Hallam University","degree_name":"dphil","degree_level":"doctoral","degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":["Goodwill, Simon","Kelley, John","Haake, Steve"],"committee_chairs":[],"committee_members":[],"year":2015,"date_issued":"2015","date_published":"2015","updated_at":"2026-07-24T06:31:06Z","subjects":[],"languages":["en"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":null,"outbound_label":null,"outbound_source":null},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Goodwill, Simon","Kelley, John","Haake, Steve"]},{"key":"dc:creator","label":"Author","values":["Hudson, Christopher"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2015"]},{"key":"dc:date.issued","label":"Date","values":["2015"]},{"key":"dc:publisher.department","label":"Dc Publisher Department","values":["Health and Wellbeing"]},{"key":"dc:publisher.institution","label":"Dc Publisher Institution","values":["Sheffield Hallam University"]},{"key":"dc:relation.isreferencedby","label":"Dc Relation Isreferencedby","values":["https://shura.shu.ac.uk/10896/"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"dc:type.qualificationlevel","label":"Dc Type Qualificationlevel","values":["doctoral"]},{"key":"dc:type.qualificationname","label":"Dc Type Qualificationname","values":["dphil"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["https://shura.shu.ac.uk/10896/1/Hudsonautomatedtracking.pdf","https://shura.shu.ac.uk/10896/9/10702823.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The current advice for a sports analyst when filming a large performance area is to use multiple fixed cameras or a single panning one. Neither of these options is ideal: multiple cameras must be positioned, have their shutters synchronised and their footage combined for analysis; a panning camera makes it difficult to determine an athlete’s movement relative to an external frame of reference. The aim of this study was to establish a process that enabled the confident, accurate and precise use of a wide field of view for measuring distance and speed in large performance areas. Swimming was used as an example sport as it had a large performance area, which measured 50 m by 25 m. A process for determining the accuracy and precision with which distance and speed could be reconstructed from a wide field of view was developed. A nonlinear calibration procedure was used to account for radial distortion. The Root Mean Square Error (RMSE) of reconstructed distances for a wide field of view was 16 x 10-3 m. This compared favourably with a three camera system reported in the literature, which had an RMSE of 46 x 10-3 m. In addition, it was shown that a wide field of view could be used to identify a 1% enhancement in speed when it was measured over 10 m or more. A wide field of view was used to capture video footage of a swimming competition. This was used to track swimmers using two methods: manual and automated. The two methods showed good agreement for mean speed, but the automated one had higher variability in instantaneous speed than did the manual."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Automated tracking of swimmers in the clean swimming phase of a race"]}]}],"canonical_facts":{"dc:contributor.advisor":["Goodwill, Simon","Kelley, John","Haake, Steve"],"dc:creator":["Hudson, Christopher"],"dc:date":["2015"],"dc:date.issued":["2015"],"dc:description.abstract":["The current advice for a sports analyst when filming a large performance area is to use multiple fixed cameras or a single panning one. Neither of these options is ideal: multiple cameras must be positioned, have their shutters synchronised and their footage combined for analysis; a panning camera makes it difficult to determine an athlete’s movement relative to an external frame of reference. The aim of this study was to establish a process that enabled the confident, accurate and precise use of a wide field of view for measuring distance and speed in large performance areas. Swimming was used as an example sport as it had a large performance area, which measured 50 m by 25 m. A process for determining the accuracy and precision with which distance and speed could be reconstructed from a wide field of view was developed. A nonlinear calibration procedure was used to account for radial distortion. The Root Mean Square Error (RMSE) of reconstructed distances for a wide field of view was 16 x 10-3 m. This compared favourably with a three camera system reported in the literature, which had an RMSE of 46 x 10-3 m. In addition, it was shown that a wide field of view could be used to identify a 1% enhancement in speed when it was measured over 10 m or more. A wide field of view was used to capture video footage of a swimming competition. This was used to track swimmers using two methods: manual and automated. The two methods showed good agreement for mean speed, but the automated one had higher variability in instantaneous speed than did the manual."],"dc:format":["application/pdf"],"dc:identifier.uri":["https://shura.shu.ac.uk/10896/1/Hudsonautomatedtracking.pdf","https://shura.shu.ac.uk/10896/9/10702823.pdf"],"dc:language":["en"],"dc:publisher.department":["Health and Wellbeing"],"dc:publisher.institution":["Sheffield Hallam University"],"dc:relation.isreferencedby":["https://shura.shu.ac.uk/10896/"],"dc:title":["Automated tracking of swimmers in the clean swimming phase of a race"],"dc:type":["Thesis"],"dc:type.qualificationlevel":["doctoral"],"dc:type.qualificationname":["dphil"]},"updated_at":"2026-07-24T06:31:06Z"}