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dc.contributor.authorJavadiha, Mohammadreza
dc.contributor.authorAndújar Gran, Carlos Antonio
dc.contributor.authorLacasa Claver, Enrique
dc.contributor.otherUniversitat Politècnica de Catalunya. Doctorat en Computació
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2023-01-24T13:21:57Z
dc.date.available2023-01-24T13:21:57Z
dc.date.issued2023-01-01
dc.identifier.citationJavadiha, M.; Andujar, C.; Lacasa, E. A query language for exploratory analysis of video-based tracking data in padel matches. "Sensors (Basel, Switzerland)", 1 Gener 2023, vol. 23, núm. 441, p. 1-28.
dc.identifier.issn14248220
dc.identifier.urihttp://hdl.handle.net/2117/380991
dc.description.abstractRecent advances in sensor technologies, in particular video-based human detection, object tracking and pose estimation, have opened new possibilities for the automatic or semi-automatic per-frame annotation of sport videos. In the case of racket sports such as tennis and padel, state-of- the-art deep learning methods allow the robust detection and tracking of the players from a single video, which can be combined with ball tracking and shot recognition techniques to obtain a precise description of the play state at every frame. These data, which might include the court-space position of the players, their speeds, accelerations, shots and ball trajectories, can be exported in tabular format for further analysis. Unfortunately, the limitations of traditional table-based methods for analyzing such sport data are twofold. On the one hand, these methods cannot represent complex spatio-temporal queries in a compact, readable way, usable by sport analysts. On the other hand, traditional data visualization tools often fail to convey all the information available in the video (such as the precise body motion before, during and after the execution of a shot) and resulting plots only show a small portion of the available data. In this paper we address these two limitations by focusing on the analysis of video-based tracking data of padel matches. In particular, we propose a domain-specific query language to facilitate coaches and sport analysts to write queries in a very compact form. Additionally, we enrich the data visualization plots by linking each data item to a specific segment of the video so that analysts have full access to all the details related to the query. We demonstrate the flexibility of our system by collecting and converting into readable queries multiple tips and hypotheses on padel strategies extracted from the literature.
dc.format.extent28 p.
dc.language.isoeng
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subject.lcshPaddle tennis
dc.subject.lcshRacket games
dc.subject.otherSports science
dc.subject.otherRacket sports
dc.subject.otherVideo-based analysis
dc.subject.otherPlayer tracking
dc.subject.otherSport analytics
dc.subject.otherData analysis
dc.subject.otherData visualization
dc.titleA query language for exploratory analysis of video-based tracking data in padel matches
dc.typeArticle
dc.subject.lemacPàdel
dc.subject.lemacEsports de raqueta
dc.contributor.groupUniversitat Politècnica de Catalunya. ViRVIG - Grup de Recerca en Visualització, Realitat Virtual i Interacció Gràfica
dc.identifier.doi10.3390/s23010441
dc.relation.publisherversionhttps://www.mdpi.com/1424-8220/23/1/441
dc.rights.accessOpen Access
local.identifier.drac35067627
dc.description.versionPostprint (published version)
local.citation.authorJavadiha, M.; Andujar, C.; Lacasa, E.
local.citation.publicationNameSensors (Basel, Switzerland)
local.citation.volume23
local.citation.number441
local.citation.startingPage1
local.citation.endingPage28


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