Autonomous Vehicles

In-Cabin Monitoring

Driver and occupant monitoring datasets for safety, compliance, and premium in-vehicle experiences. We label gaze, posture, hands, and in-cabin events across diverse lighting and camera setups.

Core Capabilities

Gaze & Head Pose Estimation

Keypoint and landmark annotation to train models that detect where a driver is looking and for how long.

Drowsiness & Distraction Detection

Labeling yawns, blinks, phone usage, and posture changes across day/night and IR camera feeds.

Hands-on-Wheel Monitoring

Tracking hand location and steering wheel interaction for SAE-compliant driver supervision systems.

Seatbelt & Occupancy Detection

Bounding boxes and classification for seatbelt usage, occupant presence, and child-seat identification.

In-Cabin Event Detection

Temporal labeling of events like smoking, eating, aggressive behavior, and emergency gestures.

Privacy-Aware Annotation

PII-safe workflows with face blurring options and strict access controls for sensitive in-vehicle footage.

Data Annotation Use Cases in In-Cabin Monitoring

Annotation & labeling of data can serve a variety of purposes within In-Cabin Monitoring, from enabling critical computer vision to gaining a better sense of the surroundings for AI initiatives.

The following use cases provide more insight into how our data annotation & labeling expertise can benefit your In-Cabin Monitoring operations: