Tangible Play / Osmo · September 2019 – February 2023
Computer Vision Product Systems
Real-time CV systems for education products under device and usability constraints.
Role: Senior Research Engineer / CV lead
Executive summary
Led CV systems that improved worksheet recognition accuracy and supported interactive learning workflows.
Problem and constraints
Education products required reliable computer vision under varied lighting, paper positions, device constraints, and real-time interaction expectations.
- Device performance
- Real-world lighting
- Low-latency interaction
- High recognition accuracy
- Product feedback loops
Architecture
Decision Theater
Decision fork
Offline accuracy vs product-fit model
A model that wins offline but misses latency constraints fails the product.
Chosen: Production-fit CV system. Interactive learning depends on reliable user experience, not leaderboard-only accuracy.
Evaluation and reliability
- Tracked worksheet recognition accuracy improvement and real-time shaded-region IoU.
Observability and debugging
- Product usage and engagement outcomes guided CV system iteration.
Reflection
This work proves ML product depth outside the LLM trend cycle: real users, device constraints, deployment, and feedback loops.
This case study uses sanitized architecture and representative examples. It excludes confidential prompts, customer data, proprietary datasets, private implementation details, and internal traces.