
Automating Sports Video Clipping with Fox Sports
Join Stephanie Gooch, Senior Optimization Solutions Architect Advocate at AWS, and Han from the PACE team as they explore how Fox Sports automated their sports video clipping process using AWS services. This episode of "How to Build with AWS" showcases a real-world application of AI to streamline content creation for social media.
Introduction:
Join Stephanie Gooch, Senior Optimization Solutions Architect Advocate at AWS, and Han from the PACE team as they explore how Fox Sports automated their sports video clipping process using AWS services. This episode of "How to Build with AWS" showcases a real-world application of AI to streamline content creation for social media.
Key Takeaways:
- Challenge Identification: Fox Sports faced significant delays in posting highlight clips to social media due to manual curation and editing processes.
- Solution Overview: The solution leverages AWS Elemental MediaLive, Elemental Inference, and a serverless architecture to automate the detection and clipping of key moments in live sports broadcasts.
- Technical Details: The system uses custom-trained machine learning models to identify key moments and smart cropping to convert landscape videos into portrait format for social media.
- Prototype Development: The PACE team developed a polished prototype within 4-6 weeks, focusing on speed and functionality to meet Fox Sports' requirements.
- User Experience: The end-to-end application allows media teams to view, edit, and download clips directly, significantly reducing manual effort and latency.
- Security and Efficiency: The solution incorporates robust security measures, including WAF protection and pre-signed S3 URLs, and is built on an event-driven, serverless architecture to optimize resource usage.
- Future Potential: The architecture is scalable and could be extended to support different types of events beyond sports, such as news broadcasts or reality TV.
Call to Action:
Don't miss out on the valuable insights and demonstrations from this episode. Watch the on-demand live stream and explore the GitHub repo to learn more about implementing this solution.
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