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Sports Photography Company Streamlining Editing with Shade.ai Integration
Company Situation
This company operates within the sports photography industry, managing a team of photographers covering major sporting events such as collegiate basketball tournaments and professional leagues like the NFL and NBA. Their workflow involves handling high volumes of high-resolution images captured across multiple cameras simultaneously during fast-paced live events.
Existing Workflow
Photographers capture thousands of frames per game, often shooting bursts of around 30 frames per second. Immediately after capture, photos are transferred to an on-location server, where automated Photoshop scripts apply color corrections. Edited photos are then uploaded to Dropbox for company access in near real-time. Post-event, the company manually reviews and flags preferred images using Lightroom, significantly reducing the photo pool from thousands to a few hundred. Subsequently, these selected images are uploaded to a custom web server, where a proprietary application allows manual tagging of players by cross-referencing rosters and jersey numbers. Finally, companies access the images through a web portal filtering by year, player, and jersey number.
Issues with the Existing Workflow
The company’s current process is labor-intensive and time-consuming, especially the manual tagging of players in thousands of photos after events. This middle step requires significant human effort to associate metadata such as player names and numbers, which is complicated by partial visibility of jersey numbers or obstructed player faces during fast game action. Additionally, the existing storage and delivery system relies on Dropbox and custom-built tools, which fragment the workflow and limit scalability.
How Shade Would Change Their Workflow
Shade would replace the Dropbox component of the workflow, serving as a centralized platform for uploading, storing, tagging, reviewing, and archiving photos. With Shade’s AI-powered metadata capabilities, the system can automatically recognize faces and jersey numbers at the point of ingestion, drastically reducing the need for manual tagging. This automatic tagging would leverage pre-uploaded rosters with player images and numbers to accurately identify players despite visual challenges. Shade consolidates multiple tools into one platform, streamlining the entire asset management process while maintaining flexibility for delivery and company access.
Benefits
- Significant reduction in manual labor required for metadata tagging
- Faster turnaround from photo capture to company access with AI-powered automation
- Centralized platform replacing disparate tools like Dropbox and custom servers
- Improved accuracy in player identification through facial recognition and jersey number detection
- Scalable and efficient management of large volumes of creative assets
- Enhanced ability to archive, search, review, and approve content in one place