An open‑source interface for preprocessing, anonymizing, and securing multi‑source training data for humanoid robots

CogniCap Studio — Open-Source Anonymization & Preprocessing Interface for Humanoid Robot Training Data

Abstract

CogniCap Studio will be an open-source, locally-run application giving researchers and data collectors a visual interface to review, trim, and anonymize raw multimodal footage before it leaves their device — ensuring that real-world physical skill data can be collected ethically and shared safely for humanoid robot training.

Hypothesis

The primary bottleneck in embodied AI is not compute — it is the lack of clean, privacy-compliant, real-world sensorimotor data. We hypothesize that by removing the technical barrier to safe data collection and anonymization, CogniCap Studio can accelerate the creation of physical AI datasets the same way early annotation tools accelerated computer vision research.

The Problem

Teaching robots physical skills requires recording real humans in real environments — workshops, kitchens, clinics. This footage inevitably captures faces, documents, and other identifying information. Without accessible tooling to handle this, valuable training data goes uncollected or unusable due to privacy risk.

The Solution

During the hackathon, a working prototype of CogniCap Studio will be built around three modules:
Ingest & Review — load stereo video footage and optional sensor streams (accelerometer CSV), preview on a frame-accurate timeline with variable playback speed, and trim unwanted scenes.
Smart Anonymization — automatic face detection on import via MediaPipe. For other sensitive objects, the operator draws one bounding box; Meta’s SAM2 then tracks and masks it automatically across the entire clip.
Secure Export — cleaned footage exported in robotics-compatible formats (MP4 + CSV or HDF5), ready for downstream processing and training pipelines.

Equipment

Dual-webcam stereo rig and a standard laptop running the full pipeline locally, with pre-recorded footage as the primary demo asset.

Why It Matters

Sensorimotor data — how humans see and physically interact with the world — is the missing training resource for the next generation of robots. CogniCap Studio will provide the secure, privacy-first client layer that makes collecting this data at scale realistic for anyone, without requiring data engineering expertise or cloud infrastructure.