PRIVACY CAM / ON-DEVICE SECURE WORKSPACE
AnonCam Studio
Anonymize faces and clean backgrounds in real-time. Apply blur, pixelation, or emojis to detected faces, and blur or strip backgrounds. 100% browser-based with zero server uploads.
Private PRIVACY & ANONYMIZATION STUDIO
Securely Anonymize Faces & Video Backgrounds
AnonCam Studio is a browser-based, client-side application designed to strip away facial identification and background data before you publish. Protect identity, prevent data profiling, and craft clean presentations with complete privacy.
How it works
- Load a portrait image or enable your webcam.
- Select a face filter: apply Blur, Pixelate or overlay Emoji stickers.
- Configure background filter: blur background, synthesize a gradient backdrop, or strip it away for transparency.
- Click **Start Recording** to capture video, or **Download PNG** to save a photo.
Use Cases
- **Vlogging**: Anonymize bystanders or children in street logs.
- **Interviews**: Maintain anonymity for sensitive sources or focus groups.
- **Professional Demos**: Hide private room settings or home backgrounds.
- **Social Media**: Create fun emoji-masked videos and avatars.
Unlike standard video editors, AnonCam Studio processes every frame locally within your browser using WebAssembly. No media data is ever uploaded, guaranteeing 100% privacy and safety.
FAQ
Is my webcam stream saved to any database?
No. The webcam stream is strictly processed frame-by-frame on your device. Cravveo does not host any backend media servers, ensuring your stream stays private.
What video format is exported during recording?
Recording outputs a standard WebM (.webm) video format natively supported by browsers. You can convert it to MP4 using standard editors or upload it directly to sharing networks.
Why does the face filter sometimes flicker?
Very fast movements, low lighting, or profile views can make face detection briefly lose tracking. Ensure good lighting and face the camera directly for steady tracking.
Does it require high system specifications?
It uses lightweight TensorFlow Lite models (BlazeFace and Selfie Segmenter) running via WebAssembly. Most modern laptops and smartphones will easily render the stream at 24-30 FPS.