Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments

Video-based trajectory analysis might be rather well discussed in sports, such as soccer or basketball, but in cycling, this is far less common. In this paper, a video processing pipeline to extract riding lines in cyclocross races is presented. The pipeline consists of a stepwise analysis process t...

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Autores principales:	Jelle De Bock, Steven Verstockt
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	pose estimation sports object detection sports data analysis Chemical technology TP1-1185
Acceso en línea:	https://doaj.org/article/b2f1525ead9f4306a3e170c859915328
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id	oai:doaj.org-article:b2f1525ead9f4306a3e170c859915328
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spelling	oai:doaj.org-article:b2f1525ead9f4306a3e170c8599153282021-11-25T18:57:58ZVideo-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments10.3390/s212276191424-8220https://doaj.org/article/b2f1525ead9f4306a3e170c8599153282021-11-01T00:00:00Zhttps://www.mdpi.com/1424-8220/21/22/7619https://doaj.org/toc/1424-8220Video-based trajectory analysis might be rather well discussed in sports, such as soccer or basketball, but in cycling, this is far less common. In this paper, a video processing pipeline to extract riding lines in cyclocross races is presented. The pipeline consists of a stepwise analysis process to extract riding behavior from a region (i.e., the fence) in a video camera feed. In the first step, the riders are identified by an Alphapose skeleton detector and tracked with a spatiotemporally aware pose tracker. Next, each detected pose is enriched with additional meta-information, such as rider modus (e.g., sitting on the saddle or standing on the pedals) and detected team (based on the worn jerseys). Finally, a post-processor brings all the information together and proposes ride lines with meta-information for the riders in the fence. The presented methodology can provide interesting insights, such as intra-athlete ride line clustering, anomaly detection, and detailed breakdowns of riding and running durations within the segment. Such detailed rider info can be very valuable for performance analysis, storytelling, and automatic summarization.Jelle De BockSteven VerstocktMDPI AGarticlepose estimationsportsobject detectionsports data analysisChemical technologyTP1-1185ENSensors, Vol 21, Iss 7619, p 7619 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	pose estimation sports object detection sports data analysis Chemical technology TP1-1185
spellingShingle	pose estimation sports object detection sports data analysis Chemical technology TP1-1185 Jelle De Bock Steven Verstockt Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
description	Video-based trajectory analysis might be rather well discussed in sports, such as soccer or basketball, but in cycling, this is far less common. In this paper, a video processing pipeline to extract riding lines in cyclocross races is presented. The pipeline consists of a stepwise analysis process to extract riding behavior from a region (i.e., the fence) in a video camera feed. In the first step, the riders are identified by an Alphapose skeleton detector and tracked with a spatiotemporally aware pose tracker. Next, each detected pose is enriched with additional meta-information, such as rider modus (e.g., sitting on the saddle or standing on the pedals) and detected team (based on the worn jerseys). Finally, a post-processor brings all the information together and proposes ride lines with meta-information for the riders in the fence. The presented methodology can provide interesting insights, such as intra-athlete ride line clustering, anomaly detection, and detailed breakdowns of riding and running durations within the segment. Such detailed rider info can be very valuable for performance analysis, storytelling, and automatic summarization.
format	article
author	Jelle De Bock Steven Verstockt
author_facet	Jelle De Bock Steven Verstockt
author_sort	Jelle De Bock
title	Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
title_short	Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
title_full	Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
title_fullStr	Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
title_full_unstemmed	Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments
title_sort	video-based analysis and reporting of riding behavior in cyclocross segments
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/b2f1525ead9f4306a3e170c859915328
work_keys_str_mv	AT jelledebock videobasedanalysisandreportingofridingbehaviorincyclocrosssegments AT stevenverstockt videobasedanalysisandreportingofridingbehaviorincyclocrosssegments
_version_	1718410484415201280

Video-Based Analysis and Reporting of Riding Behavior in Cyclocross Segments

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