--- title: "Egocentric Video" description: "" url: "https://unidata.pro/data-collection/egocentric-video-data/" date_modified: "2026-06-05T11:02:01+03:00" language: "en-US" --- ## List of Points - **text description:** Leading Data ProvidersAhead of Robotics Trends - **text description:** Scalable CollectionCustom Data Collection - **text description:** 100%Consented participants ## Section Heading: Questions End-to-End Egocentric Data Collection Workflow ## Description of the Facts Section From capture to delivery, we build complete egocentric data collection workflows tailored to your model — for embodied AI, robotics, AR/VR, and multimodal foundation models. ## List of Questions - **Question:** Discovery & Scoping — **Additional fields in the invoice:** - **Text on the second line:** We align with the client's model goals, target scenarios, and use case to define data requirements before capture begins. - **Question:** Egocentric Capture — **Additional fields in the invoice:** - **Text on the second line:** First-person recordings collected with head-mounted cameras (Pico 4 Ultra, ZED) and IMU trackers in different setups, across real-world and controlled capture environments. - **Question:** Capture Validation — **Additional fields in the invoice:** - **Text on the second line:** Sessions are validated on-site for sensor synchronization, scenario completeness, and protocol compliance. - **Question:** Auto-Pose Generation — **Additional fields in the invoice:** - **Text on the second line:** 3D pose data in quaternion format is generated automatically from onboard sensor fusion. No manual annotation required. - **Question:** Client Review & Iteration — **Additional fields in the invoice:** - **Text on the second line:** Continuous client sync throughout the project. As requirements shift, we realign scenarios, capture conditions, and protocols mid-flight. - **Question:** Data Synchronization & Delivery — **Additional fields in the invoice:** - **Text on the second line:** Time-aligning video, IMU streams, and pose data into structured, training-ready files in the client's preferred format. - **Question:** Ongoing Support — **Additional fields in the invoice:** - **Text on the second line:** Post-delivery support for retraining cycles, scenario expansion, and incremental capture as the client's model evolves. ## Section Heading: Challenges Data Struggles? Let's Fix That ## List of Challenges Provisions - **Data:** ### The problem - **Volume isn’t enough.** Plenty of first-person video exists, but most of it is unusable noise. - **2D data for a 3D problem.** Flat GoPro footage with no camera position or lens data — useful only for pretraining. - **Lab setups don’t transfer.** Controlled lighting and scripted actors don’t reflect real homes or workplaces. - **No body, no hands.** Without skeleton and hand pose, action recognition is guesswork — you see what, never how. - **Data:** ### What Unidata delivers - **Curated, ML-ready by default.** 15,000+ scenarios across 7 room types and 90+ functional zones, with auto-generated pose data. - **Stereo capture with depth maps.** Pico 4 Ultra delivers 6 synchronized streams for real-world 3D and spatial geometry. - **Real + controlled environments.** Structured scenarios captured in actual homes and kitchens — real backgrounds, real lighting, real motion. - **Full-body skeleton + hand poses.** Motion trackers on hands, feet, and pelvis. Full-body pose out of the box. ## Section Heading: Questions - Take 2 FAQ ## List of Questions - Take 2 - **Question:** Can we license the existing 15,000 scenarios as-is? — **Answer:** Yes. The base dataset is available under a commercial license, with full multi-modal data — RGB, depth, pose, and annotations. We can also slice it by scenario type, environment, or participant demographics for your needs. - **Question:** Do you do custom data collection? — **Answer:** Custom collection is the other half of what we do. Send us your task definitions, environment requirements, equipment list — we'll scope, price, and schedule. Most projects start delivering within two weeks. - **Question:** What's the licensing situation for the participants? — **Answer:** Every participant signs a commercial-use release before recording. Faces, voices, and home interiors are cleared for use in training data, model evaluation, and downstream commercial AI products. - **Question:** What output formats are supported? — **Answer:** Standard delivery includes .mp4 video, .rrd (Rerun) for visualization, .json metadata and annotation files, and pose/hand keypoint files. Other formats (Parquet, WebDataset, custom schemas) are available on request. - **Question:** Why are tactile sensors on the roadmap — is hand pose not enough? — **Answer:** For many tasks, pose is sufficient. But real robots have tactile sensors on their manipulators for a reason: objects that look visually uniform can have uneven weight distribution — one side heavier than the other — and a robot needs to feel that, not just see it. Tactile data captures grip pressure, surface texture, and load asymmetry that no camera can provide. We're working on integrating instrumented gloves so the egocentric dataset can eventually cover this layer too. - **Question:** Can we see real data before signing anything? — **Answer:** Yes — we publish live Rerun viewer links to actual scenario recordings. No gated demos, no NDA before evaluation. Click "Explore sample data" at the top of the page. ## Section Heading: How the Data Looks How The Data Looks ## Description of the "How the Data Looks" Section Every scenario ships as a synchronized multi-modal package — RGB streams, depth maps, skeleton poses, and structured annotations. Open in Rerun or export to your own pipeline. ## List of Materials: How The Data Looks - **Tab:** Pico 4 Ultra + Motion Trackers — **List of Files:** - **Preview:** ![](https://unidata.pro/wp-content/uploads/2026/06/pico-4-ultra-motion-trackers-how-the-data-looks-2.webp) - **Text in the right-hand side of the example:** {"notice":"This is the timestamp and head pose information when obtaining the image for the first frame.","timeStampNs":1777014188181698048,"cameraExtrinsics":"[-9.628797603298362E-5, -0.9999956870558201, 0.002935404296600524, -0.020576731121003326, -0.9999901031255084, 8.323003728472929E-5, -0.004448227039627642, 0.08285444730230307, 0.004447963540863667, -0.0029358035560512006, -0.9999857982380652, -0.016863868701343578, 0.0, 0.0, 0.0, 1.0]|[-9.628797603294295E-5, -0.9999956870558203, 0.0029354042966005297, -0.020582891123388035, -0.9999901031255085, 8.323003728477016E-5, -0.004448227039627643, 0.01888029732300786, 0.004447963540863666, -0.0029358035560511976, 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- **Tab:** Pico 4 Ultra + Motion Trackers + ZED — **List of Files:** - **Preview:** ![](https://unidata.pro/wp-content/uploads/2026/06/pico-4-ultra-motion-trackers-zed-how-the-data-looks.webp) - **Text in the right-hand side of the example:** {"notice":"This is the timestamp and head pose information when obtaining the image for the first frame.","timeStampNs":1775028127553583872,"cameraExtrinsics":"[0.004226368795699256, -0.9999461237645672, 0.009480895264669182, -0.021195964498222083, -0.9999908192954877, -0.004219479484407838, 7.465370854613225E-4, 0.08271580207501084, -7.064924217904565E-4, -0.009483963364414072, -0.9999547766311039, -0.017584167115639763, 0.0, 0.0, 0.0, 1.0]|[0.004226368795699258, -0.9999461237645678, 0.009480895264669182, -0.020924610514302097, -0.9999908192954877, -0.004219479484407841, 7.465370854613207E-4, 0.01851139734455566, -7.064924217904583E-4, -0.009483963364414075, -0.999954776631104, -0.017629527457467292, 0.0, 0.0, 0.0, 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## Title: How We Capture How We Capture ## Description: How We Capture Stereo video, 3D depth, and full-body pose — six streams, all synchronized in real time. ## List of "How We Capture" cards - **Colored Stitch:** Head-Mounted — **Title:** Pico 4 Ultra — **Description:** High-resolution stereo passthrough with hand tracking. Captures the wearer's true field of view at 30FPS, with depth and 6DoF pose data on every frame. — **Tag Cloud:** - Stereo passthrough - Hand tracking - 6dof pose - Depth maps — **Image:** ![](https://unidata.pro/wp-content/uploads/2026/06/pico-4-ultra.webp) - **Colored Stitch:** Body tracking — **Title:** Motion Trackers — **Description:** IMU trackers mounted on wrists, ankles, and pelvis. Together with the headset they reconstruct a full-body skeleton — every joint position captured in real time. — **Tag Cloud:** - Full-body skeleton - 5 trackers - Real-time pose - Joint positions — **Image:** ![](https://unidata.pro/wp-content/uploads/2026/06/motion-trackers.webp) - **Colored Stitch:** Depth / RGB — **Title:** ZED Stereo Camera — **Description:** Stereo and single-lens cameras capturing depth, 3D scene detail, and hand-level views in real time.In our ZPT setup: ZED X Mini ZED X One ×3 — **Tag Cloud:** - Object tracking - Time-synced - 6dof pose - Depth maps — **Image:** ![](https://unidata.pro/wp-content/uploads/2026/06/zed-stereo-camera.webp) ## Title: Ego Numbers Egocentric Video In Numbers ## List of Ego Numbers - **Stripe Color:** #259cf4 — **Background Color:** ![](https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-in-numbers-1.webp) — **Title:** 15 000 — **Signature:** Scenarios Collected - **Stripe Color:** #7a7afb — **Background Color:** ![](https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-in-numbers-2.webp) — **Title:** 4 000 — **Signature:** Hours of Recordings - **Stripe Color:** #ffcb3b — **Background Color:** ![](https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-in-numbers-3.webp) — **Title:** 03 — **Signature:** device types - **Stripe Color:** #ff85e3 — **Background Color:** ![](https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-in-numbers-4.webp) — **Title:** 02 — **Signature:** Unique Setups - **Stripe Color:** #8486a7 — **Background Color:** ![](https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-in-numbers-2.webp) — **Title:** 06 — **Signature:** synchronized devices ## Title: Ego Videos Egocentric Video Dataset ## Description of Ego Videos 4,050 hours of first-person video capturing daily activities in real environments. ## Image from Ego Videos ![](https://unidata.pro/wp-content/uploads/2026/07/annotated_item3_yellow.webp) ## Ego Videos Editor ### Highlights: - 4,050 hours across 13 household scenarios - Pico 4 Ultra + ZED + motion trackers with synchronized IMU - Quaternion-based 3D pose for egocentric tracking - Real homes: kitchens, bathrooms, living rooms ## Ego Videos Link [https://drive.google.com/drive/folders/1XKuVs7T7cAbc7jT4yiyGHUzEPrYRDM8c](https://drive.google.com/drive/folders/1XKuVs7T7cAbc7jT4yiyGHUzEPrYRDM8c) ## A quote in the blockquote section The market keeps asking for more data, but the data they have is broken. I wanted a setup that would make collection highly relevant relevant — not just for now, but for the future. ## FI in the blockquote section Martinian Letunovsky ## position in the blockquote section Head of IT Department ## Image of a reviewer ![](https://unidata.pro/wp-content/uploads/2026/06/martinian-letunovsky-new.webp) ## Block: Hero **Title:** Egocentric Video Data Collection for AI Training **Description:** Custom egocentric data collection for AI training. Multi-camera wearable rigs (Pico 4 Ultra, ZED, Motion Trackers) and trained capture teams deliver synchronized first-person video and 3D pose data, built around your model and scenarios. **Video File - Main Section:** https://unidata.pro/wp-content/uploads/2026/06/egocentric-video-szhatoe.mp4 ## Section Heading: Industries Industries ## List of Industries - **Industry Headline:** Embodied AI & Robotics — **Industry Description:** Real-world video of humans handling objects, teaching robots manipulation and mobility. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/embodied-ai-robotics-ego.webp) - **Industry Headline:** AR / VR Systems — **Industry Description:** Head-mounted capture that grounds spatial computing, hand tracking, and immersive UX. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/ar-vr-systems-ego.webp) - **Industry Headline:** Autonomous Systems — **Industry Description:** Synchronized multi-sensor streams that train agents to perceive, plan, and act safely. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/autonomous-systems-ego.webp) - **Industry Headline:** Human Activity Understanding — **Industry Description:** Annotated daily activities that train models to recognize intent and segment actions. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/human-activity-understanding-ego.webp) - **Industry Headline:** Smart Home & Assistive Tech — **Industry Description:** Real-home eye-level interactions powering assistants, fall detection, and home automation. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/smart-home-assistive-tech-ego.webp) - **Industry Headline:** Industrial Training & Workforce — **Industry Description:** Wearable capture of field work powering AR instructions and on-the-job copilots. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/industrial-training-workforce-ego.webp) - **Industry Headline:** Foundation & World Models — **Industry Description:** Large-scale real-world video with motion and depth, fuel for physical-world reasoning. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/foundation-world-models-ego.webp) - **Industry Headline:** Healthcare & Eldercare — **Industry Description:** First-person clinical recordings for surgical assistance and AI-assisted diagnostics. — **An Overview of the Industry:** ![](https://unidata.pro/wp-content/uploads/2026/06/healthcare-eldercare-ego.webp) ## Section Heading: Real Real homes. Real people. Real interactions. ## List of cards in the "real" section - **title:** Diverse participants — **description:** Mixed age and gender across hundreds of contributors. Every recording is consented and licensed for commercial use. — **color under svg:** #fff3fc - **title:** Real + controlled environments — **description:** Captured in-the-wild — actual homes and kitchens, not clean lab setups. Lighting variation, clutter, and realistic human motion are features, not bugs. — **color under svg:** #fff5ea - **title:** Stratified scenarios — **description:** 15,000+ structured tasks across coffee-making, cooking, object handling, and everyday chores — designed for embodied AI training. — **color under svg:** #f1f1ff ## Ticker - **text:** Loading dishwasher - **text:** Folding laundry - **text:** Opening a jar - **text:** Wiping a counter - **text:** Boiling water - **text:** Setting the table ## Title: Our Setup Inside Our Capture Setup ## Our Setup Cards ![Setup 1](https://unidata.pro/wp-content/uploads/2026/06/pico-4-ultra-motion-trackers-zed-2.webp) ![Setup 2](https://unidata.pro/wp-content/uploads/2026/06/pico-4-ultra-motion-trackers.webp) ## Section heading: production How we run production-grade capture ## Description of the "production" section Every session is a coordinated operation — actor briefing, environment prep, multi-device sync check, and quality review before a single clip ships. ## List of media in the "Production" section - **preview:** ![](https://unidata.pro/wp-content/uploads/2026/06/how-we-run-production-grade-capture-prevyu-1.webp) - **preview:** ![](https://unidata.pro/wp-content/uploads/2026/06/how-we-run-production-grade-capture-prevyu-2.webp) ## Section heading: Exactly See Exactly What You're Buying ## Link in the "Exactly" section [https://rerun.io/viewer?url=https%3A%2F%2Fsample-datasets.storage.yandexcloud.net%2FRobots-promo%2Fego-rerun-v1-1%2Frerun_v1_20260317_001624.rrd%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256](https://rerun.io/viewer?url=https%3A%2F%2Fsample-datasets.storage.yandexcloud.net%2FRobots-promo%2Fego-rerun-v1-1%2Frerun_v1_20260317_001624.rrd%3FX-Amz-Algorithm%3DAWS4-HMAC-SHA256) ## Specifications in the "Exactly" section - **characteristic:** Format — **value:** .mp4, .rrd, .json - **characteristic:** Madalities — **value:** RGB, Depth, Pose, Hands - **characteristic:** Capture — **value:** Pico 4 Ultra - **characteristic:** AVG Duration — **value:** 2–6 min / scenario - **characteristic:** Annotation — **value:** Scene, Action , Object, Hand pose - **characteristic:** Licence — **value:** Commercial, 100% consented ## background in the "Exactly" section ![](https://unidata.pro/wp-content/uploads/2026/04/background-pattern.webp) ## Preview for the "Exactly" section ![](https://unidata.pro/wp-content/uploads/2026/06/see-exactly-what-youre-prevyu.webp) ## Section Title (Optional) Related Datasets ## Selecting Datasets for Output - [Egocentric Video Dataset](https://unidata.pro/datasets/egocentric-video/) - [3D Residential Scans Dataset](https://unidata.pro/datasets/3d-residential-scans/) - [Lerobot SO-101 Manipulations Dataset](https://unidata.pro/datasets/lerobot-so-101-manipulations/) - [Robotic Household Activities Dataset](https://unidata.pro/datasets/robotic-household-activities/) [Full list of this site's AI-readable pages](https://unidata.pro/llms.txt)