AI Data Operations
Expert-labeled first-person data for AI models that need to learn how humans see, move, act, interact, and navigate the physical world.
Capabilities
Precise data annotation of first-person video, sensor, and motion data, purpose-built for the AI models that handle hands, gaze, and task structures.
CAPABILITY / 01
Our egocentric data annotation experts mark hand and finger joint positions across frames in both 2D and 3D, giving robotics and AR/VR models the data required for manipulation and gesture recognition tasks.
Our egocentric data annotation experts label the point of contact, grip, and interaction sequence between a hand and an object, capturing the full interaction rather than a single static frame, so imitation-learning models can learn how a task is actually performed.
Our egocentric data annotation experts classify the specific grasp being used, for example, power grip, pinch grip, or lateral grip, supporting robotic manipulation models that need to replicate human-like grasping strategies.
Our egocentric data annotation experts create pixel-level masks isolating hands from the rest of the scene, providing the clean hand-region data that downstream pose and interaction AI models depend on.
Our egocentric data annotation experts identify whether the left or right hand is performing an action, a distinction that matters directly for bimanual manipulation and coordination AI models.
HAVE A SPECIFIC REQUIREMENT?
Tell us what your model needs. We’ll help you scope the annotation capabilities that fit your project.
Structured action and interaction data that teaches robots how a task is performed.
Hand, gaze, and scene data annotated to support natural interaction AI models on wearable and augmented-reality or virtual reality devices.
Segmentation and tracking data that helps robots recognize and safely respond to the people working alongside them.
Object and activity annotation supporting perception models deployed on autonomous or robotic platforms operating in real-world industrial environments.
Frame-level mapping of operator actions to defined Standard Operating Procedure steps, supporting process monitoring and workflow automation models.
Pose and motion annotation supporting models that track patient movement and recovery progress over time.
Hand-object interaction and procedural step annotation capturing how a task in the kitchen is actually carried out, step by step.
Full-body pose and trajectory annotation from a first-person viewpoint, supporting performance and technique analysis models.
Gaze and activity annotation supporting models that analyze how shoppers move through and interact with retail environments.
Goal-step hierarchy annotation that breaks a skilled task into its component steps, supporting instructional and skill-transfer AI models.
Head and camera pose tracking data supporting SLAM-based navigation and trajectory-prediction models.
Gaze, activity, and narration annotation supporting research models that study human attention and decision-making.
Activity and interaction annotation supporting behavioral research models focused on early developmental patterns.
Dense narration and activity captioning that convert long, continuous first-person footage into a structured, searchable record of events.
Object and scene annotation supporting models that identify hazards and monitor compliance with safety procedures in the workplace.
Hand pose and gesture annotation supporting models that translate hand movement into interface commands.
Backed by deep domain expertise across 20+ industry verticals, we collect and annotate data your models can rely on.
We audit, correct and validate auto-annotated aerial data against your guidelines before it reaches your training pipeline.
Whether you need precisely annotated training data, real-world data collection, a dedicated in-house team, or other staffing solutions, Qualitas Global delivers all three under one roof. Backed by over a decade of experience, we back every engagement with a risk-free 2-day pilot before you commit.
