Cricket Player Recognition

Sports

2018-2019

United Kingdom

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Overview

This project involves the development of an advanced object recognition system designed to identify players during a cricket match. The system utilises specific movements and sound peaks as triggers to automatically start recording the game stream, ensuring key moments are captured without manual intervention. By integrating computer vision and audio detection, this solution enhances game analysis, player tracking, and performance evaluation for teams, broadcasters, and analysts.

Challenge

The client had an existing system but needed to enhance its capabilities with additional features. However, integrating new functionality into an already developed platform presented several challenges. The system required optimisation to ensure smooth performance without disrupting existing operations. Additionally, implementing new features demanded a careful approach to maintain compatibility with the core architecture. The client turned to Go Wombat to refine and expand their system, ensuring seamless integration, improved efficiency, and enhanced usability while maintaining stability and performance.

Solution

To enhance the system's functionality, Go Wombat addressed key computer vision challenges, including object recognition and counting. We optimised the system’s performance to ensure accurate and efficient processing. Additionally, we developed a custom script for Raspberry Pi, enabling seamless streaming to a server. This allowed for real-time video redirection from the server to Facebook Live, improving accessibility and engagement. Our solution ensured smooth integration of these enhancements while maintaining the system’s stability and performance.

Result

With Go Wombat’s enhancements, the object recognition system now delivers more accurate player recognition during cricket games, significantly improving detection reliability. Additionally, we optimised system performance, ensuring smoother operation, faster processing, and increased efficiency. These improvements enable a seamless user experience and greater accuracy in real-time player tracking.

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