EGOCentric video collection

FIRST-PERSON VIDEO DATASETS

Capture high-quality egocentric video data using iMerit’s global workforce of full-time employees and iMerit Scholars. Our trained teams collect diverse, real-world first-person video tailored to AI training and evaluation needs.

Video Data Collection

VIDEO Data collection

AT SCALE

iMerit delivers enterprise-grade egocentric video data collection, curation and annotation for creating high-quality AI training data at scale for embodied AI. Our managed workforce and structured workflows ensure reliable data collection at scale, supporting the development of next-generation multi-modal and embodied AI systems.

Expert workforce

Full-time iMerit employees and Scholars capture egocentric video using standardized protocols and platforms for workflow automation.

Real-World Context

Collect authentic first-person footage across diverse environments and daily activities to create high-quality robotic foundation model training data.

Scalable Programs

Scale egocentric video creation, collection and curation programs quickly with coordinated teams, project management and centralized platforms.

Quality Assured

Multi-stage QA and clear collection guidelines ensure consistent, reliable datasets.

operational excellence

10+ years experience in providing AI data solutions by creating data pipelines through the combination if technology and human-in-loop services.

AI-Ready Data

Video data can be delivered raw or annotated, ready for model training or evaluation workflows.

Data collection CAPABILITIES

FLEXIBILE COLLECTION PROGRAMS

iMerit supports customized egocentric video collection tailored to your dataset needs.
Capabilities include:

  • First-person wearable camera capture
  • Activity-specific data collection scenarios
  • Indoor and outdoor environments
  • Structured capture protocols
  • Diverse participant demographics
  • Optional downstream annotation

EGOCENTRIC VIDEO DATA

COLLECTION, CURATION & ANNOTATION

KITCHEN ACTIVITIES

Model audit, quality control, benchmarking, bias detection and red teaming.

  • Stocking the Refrigerator
  • Cutting Vegetables
  • Cooking on Stove
  • Making Coffee
  • Preparing a Bagel
  • Sweeping Kitchen
  • Doing Dishes

HOUSEHOLD CHORES

Model audit, quality control, benchmarking, bias detection and red teaming.

  • Washing Clothes
  • Folding Laundry
  • Sorting and putting toys away
  • Vacuuming
  • Shining Shoes
  • Separating Recycling
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SKELETON TOOL

FROM RAW VIDEO TO TRAINING DATA

Ango Hub is iMerit’s enterprise-grade AI data annotation and workflow automation platform is designed to help teams build, manage, and scale high-quality training data for machine learning models. It combines automation, annotation tools, analytics, and human-in-the-loop expertise into a single system, enabling faster and more accurate AI development.
The Skeleton tool in Ango Hub is used for keypoint-based annotation, allowing annotators to label and connect points (e.g., joints in hand) to form structured skeletons for objects like humans or animals. This enables precise modeling of pose, movement, and relationships between points—especially useful in tasks like pose estimation and video-based motion tracking for humanoid and robotic arm training.

key Features

  • Keypoint annotation: Label individual points (e.g., human joints) for detailed structural representation
  • Skeleton linking (edges between points): Connect keypoints to form a defined structure (e.g., human body skeleton)
  • Pose estimation support: Designed for modeling posture, orientation, and articulation of objects
  • Consistent ontology-based structure: Uses predefined schemas to ensure uniform labeling across datasets
  • Frame-by-frame annotation (video support): Apply skeletons across frames for tracking motion in video sequences
  • Efficient labeling workflows: Structured tool and automation speed up annotation compared to free-form labeling
  • Support for complex objects: Works for humans, animals, and other articulated entities
  • Integration with broader annotation types: Can be combined with bounding boxes, polygons, or other annotation methods
  • Improved model training for motion tasks: Enables training of models for activity recognition, gesture detection, and biomechanics
  • Part of multimodal annotation ecosystem: Within Ango Hub’s broader platform supporting image, video, and other data types
“High-quality real-world data drives embodied intelligence, and consistent labeling is equally vital.”
– Head of Imaging, Humanoid Robotics Startup

Use Cases

BUILT FOR EMERGING AI APPLICATIONS

Egocentric video data enables training and evaluation across a wide range of AI systems, giving them the real-world understanding to be successful.

embodied Ai & robotics

Train models to understand real-world tasks and environments from a human perspective.

AR/VR Systems

Improve scene understanding and interaction modeling for immersive computing.

Multimodal AI Models

Develop systems that learn from video, audio, and contextual human activity.

Human Activity Understanding

Train models to recognize objects and actions in real-world environments.

CASE STUDY

Human-Centered Robot Training

Robotics startup partnered with iMerit to record, annotate, and classify real-world household task data to train next-generation humanoid robots.

Robotics startup partnered with iMerit to record, annotate, and classify real-world household task data to train next-generation humanoid robots.

The client sought a partner to coordinate 200 hours of in-home task recording using Meta Quest 3 head-mounted cameras worn by participants completing daily activities. The raw footage needed extensive structure: classification of 9 core household task types, 37 sub-classifications, and precise tracking of objects, motions, outcomes, and contextual cues.

0 hrs

Recorded household task footage

0

Task categories

0

taxonomy Subcategory
of task details

WHY WORK WITH US 

Managed global workforce

Managed service that allows you to leverage a large and diverse global workforce to create the real-world data needed for physical AI.

end-to-end solution

From talent recruitment, to data creation, collection and video annotation, iMerit combines the technology and talent into a single solution so you can focus on robotic foundation model development.

QUALITY ASSURED

Rigorous training and quality assurance processes with proven video collection protocols to ensure you’re getting the high-quality data required.

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EGOCENTRIC DATA COLLECTION TODAY!

Partner with iMerit to build high-quality egocentric video datasets tailored to your AI development needs.