---
license: cc-by-nc-nd-4.0
task_categories:
- robotics
tags:
- Physical AI
- Robotics
- egocentric vision
- pose estimations
- hands motions
size_categories:
- 1K<n<10K
---
# Egocentric Dataset  for Physical AI and Robotics
The dataset contains **4,050** hours of first-person videos for **egocentric vision** and **egocentric tracking**. Featuring multimodal data from egocentric views, it includes **data annotations** and **motion capture** for extracting **3d poses**. It provides detailed **3d objects and 3d scenes** using visual data from VR headsets to analyze **hands motions** and **pose estimations**. .- **[Get the data](https://unidata.pro/datasets/egocentric-video/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video)**

## Dataset characteristics:
| Characteristic | Data |
|----------------|------|
| Description | Egocentric video recordings of daily activities in home environments |
| Data types | Video |
| Tasks | Hand Activity Recognition Egocentric Action Recognition Hand-Object Interaction |
| Hours of recordings | 4,050 |
| Hardware setups | 2 |
| Setup 1 (Pico + Motion Trackers) | 2,321 hours (57.3%) — natural speed, slow-motion, and real-speed object transferring |
| Setup 2 (Zed + Pico + Motion Trackers) | 1,729 hours (42.7%) — scripted object transfer tasks with spatial depth + egocentric view |
| Scenarios | 13 (sorting unsorted items, arranging products by category, collecting items into a container, transferring from drawer to table, wardrobe & table & bag, transport box & display table, folding fabric items, lids & cookware & drawers, transferring with a spoon, transferring with tongs, packing into containers, two-handed sorting, assembly & disassembly) |
| Environments | Kitchen, bathroom, living room, and other home settings |
| Activities | Sorting, transferring, folding, assembly/disassembly, tool use, two-handed manipulation |

### 📊 Sample dataset available! For full access, [contact us](https://unidata.pro/datasets/egocentric-video/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video) to discuss purchase terms.

## Dataset structure
- Setup 1 (Pico + Motion Trackers): 2,321 hours (57.3%) — natural speed, slow-motion, and real-speed object transferring, with hands appearing as needed or always in frame for detailed kinematics.
- Setup 2 (Zed + Pico + Motion Trackers): 1,729 hours (42.7%) — scripted object transfer tasks combining spatial depth from stereo Zed cameras with egocentric view from Pico headset.


### 🧩 Like the dataset but need different data? We can collect a custom dataset just for you - learn more about our data collection services [here](https://unidata.pro/datasets/egocentric-video/?utm_source=hf-roboticss&utm_medium=referral&utm_campaign=egocentric-video)

## Similar Datasets:
1. [Robotic Household Activities Dataset](https://unidata.pro/datasets/robotic-household-activities/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video)
2. [Lerobot SO-101 Manipulations Dataset](https://unidata.pro/datasets/lerobot-so-101-manipulations/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video)
3. [Scene Scanning Video Dataset](https://unidata.pro/datasets/scene-scanning-video/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video)

## 🌐 [UniData](https://unidata.pro/datasets/egocentric-video/?utm_source=hf-robotics&utm_medium=referral&utm_campaign=egocentric-video) - your trusted data partner. Unique, accurate, thoroughly collected and annotated data designed to fuel your AI/ML success.