PLayerTV: Advanced Player Tracking and Identification for Automatic Soccer Highlight Clips
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Abstract (arXiv)
In the rapidly evolving field of sports analytics, the automation of targeted video processing is a pivotal advancement. We propose PlayerTV, an innovative framework which harnesses state-of-the-art AI technologies for automatic player tracking and identification in soccer videos. By integrating object detection and tracking, Optical Character Recognition (OCR), and color analysis, PlayerTV facilitates the generation of player-specific highlight clips from extensive game footage, significantly reducing the manual labor traditionally associated with such tasks. Preliminary results from the evaluation of our core pipeline, tested on a dataset from the Norwegian Eliteserien league, indicate that PlayerTV can accurately and efficiently identify teams and players, and our interactive Graphical User Interface (GUI) serves as a user-friendly application wrapping this functionality for streamlined use.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 21 of its 52 references that are in the map. First posted on arXiv 22 Jul 2024.
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21 of 52 references.
References · 21
- 2015You Only Look Once: Unified, Real-Time Object Detectioncited by 4,829
- 2015SSD: Single Shot MultiBox Detectorcited by 3,125
- 2021YOLOX: Exceeding YOLO Series in 2021cited by 1,064
- 2017Simple Online and Realtime Tracking with a Deep Association Metriccited by 908
- 2022Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Trackingcited by 345
- 2022BoT-SORT: Robust Associations Multi-Pedestrian Trackingcited by 313
- 2023SportsMOT: A Large Multi-Object Tracking Dataset in Multiple Sports Scenescited by 130
- 2022SoccerNet-Tracking: Multiple Object Tracking Dataset and Benchmark in Soccer Videoscited by 80
- 2023SoccerNet-Caption: Dense Video Captioning for Soccer Broadcasts Commentariescited by 57
- 2020Handwritten Optical Character Recognition (OCR): A Comprehensive Systematic Literature Review (SLR)cited by 56
- 2021PP-OCRv2: Bag of Tricks for Ultra Lightweight OCR Systemcited by 39
- 2023Iterative Scale-Up ExpansionIoU and Deep Features Association for Multi-Object Tracking in Sportscited by 29
9 more
- 2023GOAL: A Challenging Knowledge-grounded Video Captioning Benchmark for Real-time Soccer Commentary Generationcited by 28
- 2017A Survey on Content-Aware Video Analysis for Sportscited by 27
- 2022A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directionscited by 21
- 2023SoccerNet 2023 Challenges Resultscited by 20
- 2023Survey of Action Recognition, Spotting and Spatio-Temporal Localization in Soccer -- Current Trends and Research Perspectivescited by 7
- 2022MMSys'22 Grand Challenge on AI-based Video Production for Soccercited by 6
- 2020Slicing and dicing soccer: automatic detection of complex events from spatio-temporal datacited by 3
- 2022Optical tracking in team sportscited by 3
- 2023Soccer on Social Mediacited by 2
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