Concept demo — available on request
Real-time UE5 augmentation layer
Real-time UE5 augmentation layer
Overview
What it is
An augmented sports concept that spawns animations and UI elements in real time, driven by computer-vision-derived match data from live tennis play. It extends the broadcast-augmentation thinking behind my work at Sportradar into a real-time, camera-driven pipeline rather than a pre-rendered one.
Role & Contribution
Unreal Engine Developer, owning the end-to-end pipeline from data ingestion to in-engine presentation.
- Built the data pipeline connecting real-time computer vision output to in-engine events, using Python for processing and C++ for the Unreal Engine integration layer.
- Designed the animation and UI spawning system that reacts to live match data with minimal latency.
- Prototyped the architecture as a reusable pattern for real-time sports augmentation, distinct from the pre-rendered sequence pipelines used in broadcast production.
- Evaluated the trade-offs between real-time computer-vision-driven presentation and traditional scripted broadcast graphics.
Technical Details
Stack & specifications
Engine
Unreal Engine 5
Languages
C++, Python
Domain
Computer vision + real-time graphics
Focus
Data pipeline architecture
Type
Concept / R&D project
Status
In development
Impact
Result
Demonstrated a real-time, data-driven augmentation pipeline as a natural extension of broadcast tooling work — showing how the same architectural thinking applies beyond pre-rendered video generation.
Open to Senior / Lead Roles
Building a team like this?
I'm looking for Senior or Lead Unreal Engine positions where I can own architecture, tooling and mentoring at this level.