Blur attendee faces in conference B-roll

• ✓Browser-based — no install
• ✓Files never stored after processing
• ✓AI tracks subjects through motion

What you can process

Why motion-tracked blur matters

Hand-drawn masks fall apart when a plate glints, a face turns, or the camera whip-pans. BGBlur keeps adjustments on the detection so reviewers spend minutes—not hours—per clip on hygiene edits before publish, handoff, or archive.

When manual masking becomes the bottleneck

Step-by-step NLE masking works until subjects move, the camera pans, or you have ten files due before lunch. Preview detections, adjust strength, export HD, and move on.

Structured answers and FAQs

Pages that state the outcome first, then support it with short sections, tables, and questions people actually ask tend to be easier for readers—and for AI overview systems—to quote accurately. Independent research on generative-engine optimization (Princeton, 2024) highlights statistics, quotations, and clear FAQs as signals that correlate with higher visibility in AI-mediated answers—not keyword density. The FAQ block below mirrors common support questions for this topic.

How it works

1. Upload your video (MP4, MOV, M4V, AVI, MKV) or images (JPG, PNG, WebP, GIF).
2. Select blur type—faces, plates, background, objects, or prompt-based blur—and preview tracks.
3. Export in HD and publish anywhere; files are not stored after processing.

Benefits for this use case

• Protect bystanders, witnesses, and staff without roto brushes.
• Strong anonymization modes when blur alone is not enough for policy.
• Consistent results for news, legal, and training libraries.

Citations and concrete limits (formats, retention) help both readers and automated summaries verify claims quickly.