Automatic Player Face Detection and Recognition for Players in Cricket Games
In this paper, we have developed an augmented reality cricket broadcasting application that uses player face recognition during play to display player personal data. The system utilizes the AdaBoost algorithm for player and player face detection, employing a PAL based face recognition model to recog...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10472479/ |
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| author | Mahmood Ul Haq Muhammad Athar Javed Sethi Sadique Ahmad Mohammed A. ELAffendi Muhammad Asim |
| author_facet | Mahmood Ul Haq Muhammad Athar Javed Sethi Sadique Ahmad Mohammed A. ELAffendi Muhammad Asim |
| author_sort | Mahmood Ul Haq |
| collection | DOAJ |
| description | In this paper, we have developed an augmented reality cricket broadcasting application that uses player face recognition during play to display player personal data. The system utilizes the AdaBoost algorithm for player and player face detection, employing a PAL based face recognition model to recognize the faces of players on the field. The system is trained on a large dataset of cricket game footage and achieves high accuracy in detecting and recognizing players’ faces even with several conditions such as occlusion, non-uniform illumination, expression and pose variation. The system has the potential to enhance the viewing experience of cricket games by providing real-time player identification and statistics. The system can also be used in other sports to provide similar benefits. The paper discusses the system’s methodology, results, and implications for the future of sports broadcasting. Overall, the system provides a promising solution for automatic player face detection and recognition in sports broadcasting. |
| format | Article |
| id | doaj-art-095fed3810ec41929420278677dfe27f |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-095fed3810ec41929420278677dfe27f2025-01-25T00:00:16ZengIEEEIEEE Access2169-35362024-01-0112412194123310.1109/ACCESS.2024.337756410472479Automatic Player Face Detection and Recognition for Players in Cricket GamesMahmood Ul Haq0https://orcid.org/0000-0002-1514-0300Muhammad Athar Javed Sethi1https://orcid.org/0000-0001-7847-831XSadique Ahmad2https://orcid.org/0000-0001-6907-2318Mohammed A. ELAffendi3https://orcid.org/0000-0001-9349-1985Muhammad Asim4https://orcid.org/0000-0002-6423-9809Department of Computer System Engineering, UET Peshawar, Peshawar, PakistanDepartment of Computer System Engineering, UET Peshawar, Peshawar, PakistanEIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi ArabiaEIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi ArabiaEIAS: Data Science and Blockchain Laboratory, College of Computer and Information Sciences, Prince Sultan University, Riyadh, Saudi ArabiaIn this paper, we have developed an augmented reality cricket broadcasting application that uses player face recognition during play to display player personal data. The system utilizes the AdaBoost algorithm for player and player face detection, employing a PAL based face recognition model to recognize the faces of players on the field. The system is trained on a large dataset of cricket game footage and achieves high accuracy in detecting and recognizing players’ faces even with several conditions such as occlusion, non-uniform illumination, expression and pose variation. The system has the potential to enhance the viewing experience of cricket games by providing real-time player identification and statistics. The system can also be used in other sports to provide similar benefits. The paper discusses the system’s methodology, results, and implications for the future of sports broadcasting. Overall, the system provides a promising solution for automatic player face detection and recognition in sports broadcasting.https://ieeexplore.ieee.org/document/10472479/Face recognitionplayer detectioncricket |
| spellingShingle | Mahmood Ul Haq Muhammad Athar Javed Sethi Sadique Ahmad Mohammed A. ELAffendi Muhammad Asim Automatic Player Face Detection and Recognition for Players in Cricket Games IEEE Access Face recognition player detection cricket |
| title | Automatic Player Face Detection and Recognition for Players in Cricket Games |
| title_full | Automatic Player Face Detection and Recognition for Players in Cricket Games |
| title_fullStr | Automatic Player Face Detection and Recognition for Players in Cricket Games |
| title_full_unstemmed | Automatic Player Face Detection and Recognition for Players in Cricket Games |
| title_short | Automatic Player Face Detection and Recognition for Players in Cricket Games |
| title_sort | automatic player face detection and recognition for players in cricket games |
| topic | Face recognition player detection cricket |
| url | https://ieeexplore.ieee.org/document/10472479/ |
| work_keys_str_mv | AT mahmoodulhaq automaticplayerfacedetectionandrecognitionforplayersincricketgames AT muhammadatharjavedsethi automaticplayerfacedetectionandrecognitionforplayersincricketgames AT sadiqueahmad automaticplayerfacedetectionandrecognitionforplayersincricketgames AT mohammedaelaffendi automaticplayerfacedetectionandrecognitionforplayersincricketgames AT muhammadasim automaticplayerfacedetectionandrecognitionforplayersincricketgames |