Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/105399
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Applied Biology and Chemical Technology | - |
dc.creator | Fu, X | - |
dc.creator | Huang, W | - |
dc.creator | Sun, Y | - |
dc.creator | Zhu, X | - |
dc.creator | Evans, J | - |
dc.creator | Song, X | - |
dc.creator | Geng, T | - |
dc.creator | He, S | - |
dc.date.accessioned | 2024-04-12T06:52:13Z | - |
dc.date.available | 2024-04-12T06:52:13Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/105399 | - |
dc.language.iso | en | en_US |
dc.publisher | Molecular Diversity Preservation International (MDPI) | en_US |
dc.rights | © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). | en_US |
dc.rights | The following publication Fu X, Huang W, Sun Y, Zhu X, Evans J, Song X, Geng T, He S. A Novel Dataset for Multi-View Multi-Player Tracking in Soccer Scenarios. Applied Sciences. 2023; 13(9):5361 is available at https://doi.org/10.3390/app13095361. | en_US |
dc.subject | Benchmark | en_US |
dc.subject | Multi-view | en_US |
dc.subject | Soccer | en_US |
dc.subject | System | en_US |
dc.subject | Tracking | en_US |
dc.title | A novel dataset for multi-view multi-player tracking in soccer scenarios | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 13 | - |
dc.identifier.issue | 9 | - |
dc.identifier.doi | 10.3390/app13095361 | - |
dcterms.abstract | Localization and tracking in multi-player sports present significant challenges, particularly in wide and crowded scenes where severe occlusions can occur. Traditional solutions relying on a single camera are limited in their ability to accurately identify players and may result in ambiguous detection. To overcome these challenges, we proposed fusing information from multiple cameras positioned around the field to improve positioning accuracy and eliminate occlusion effects. Specifically, we focused on soccer, a popular and representative multi-player sport, and developed a multi-view recording system based on a (Formula presented.) strategy. This system enabled us to construct a new benchmark dataset and continuously collect data from several sports fields. The dataset includes 17 sets of densely annotated multi-view videos, each lasting 2 min, as well as 1100+ min multi-view videos. It encompasses a wide range of game types and nearly all scenarios that could arise during real game tracking. Finally, we conducted a thorough assessment of four multi-view multi-object tracking (MVMOT) methods and gained valuable insights into the tracking process in actual games. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Applied sciences, May 2023, v. 13, no. 9, 5361 | - |
dcterms.isPartOf | Applied sciences | - |
dcterms.issued | 2023-05 | - |
dc.identifier.scopus | 2-s2.0-85159264918 | - |
dc.identifier.eissn | 2076-3417 | - |
dc.identifier.artn | 5361 | - |
dc.description.validate | 202403 bcvc | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_Scopus/WOS | en_US |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Natural Science Foundation of China; Key Projects of Major Humanities and Social Sciences of Zhejiang’s Universities 2019–2020; Zhejiang Province’s “14th Five-Year Plan” graduate teaching reform project | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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applsci-13-05361.pdf | 12.07 MB | Adobe PDF | View/Open |
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