On-Device Real-Time Blurring (SNU Ambient AI — 1st Prize)
Real-time privacy blurring at target FPS on-device under thermal and power constraints — 1st Prize, SNU Ambient AI Competition.
Outcome. Built a mobile blurring pipeline achieving real-time FPS with consistent quality under battery and thermal limits; won 1st prize.
Role: Team member (4) · Dates: Aug–Sep 2024 · Stack: PyTorch-Mobile / NNAPI, Android, OpenCV
Highlights
- Explored model/runtime trade-offs (quantization, input scaling) with a deterministic harness for latency & quality.
- Implemented graceful degradation policies to sustain FPS under thermal throttling.
- Delivered demo app and benchmark report; coordinated split workstreams (model, runtime, UX).
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