| Autor: |
Hemanathan, D., Vanitha, R., Vishwa R., Shalini, S. |
| Předmět: |
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| Zdroj: |
Grenze International Journal of Engineering & Technology (GIJET); Jun2024, Vol. 10 Issue 2,Part 5, p5902-5909, 8p |
| Abstrakt: |
Cricket, a highly captivating sport, particularly popular in South Asian countries, heavily relies on umpires to make critical decisions in accordance with the cricket laws. Given the fallibility of human judgment, errors occasionally occur, leading to time-consuming reviews by the third umpire to ensure precision. To address this challenge, We introduce an AI-based umpiring system aimed at refining decision-making precision and fairness in cricket matches. Through the integration of computer vision and machine learning, our system scrutinizes live video feeds to provide umpires with instantaneous decision-making support. Critical events like ball trajectory and player movements are identified by computer vision algorithms, offering umpires immediate assistance. The system's capabilities evolve through continuous machine learning, leveraging historical match data to enhance accuracy progressively. A key feature includes instant replay provisions, empowering teams to contest decisions and fostering transparency. Our study underscores the transformative role of AI in sports officiating, presenting a blueprint for its adoption across various sporting domains. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
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