Recognize and Alert Drowsy or Distracted Drivers
In-cabin Humans in-motion
The Datagen Platform provides high quality, perfectly annotated visual data for tasks related to in-cabin driver action analysis
Obtaining visual data to train high-quality In-cabin Driver Monitoring Systems (DMS) and Occupant Monitoring Systems (OMS) is incredibly challenging. Not only is the data itself highly complex – involving humans interacting with specific automotive environments – but it is increasingly difficult to capture given the fast-changing landscape of privacy regulation. Given that DMS and OMS systems will be broadly deployed, it is also critical that data is high-variance and sufficiently diverse to avoid bias.
This includes accurate representations of the in-cabin environment with advanced motion and human-object interactions, for example key point estimation, facial keypoint estimation, gaze analysis, and hand pose analysis. Teams can use the platform to generate faces and full-body simulated data to quickly iterate on their model and improve its performance.
Generate faces and full-body simulated data to quickly iterate on your model and improve its performance.
Why Datagen for in-cabin automotive
Driver Monitoring Systems (DMS)
Systems consist of a series of small cameras or sensors to monitor driver behaviors and issue alerts or warnings when drivers show signs of drowsiness, distraction, or inattention.
Occupant-Monitoring Systems (OMS)
OMS understand the occupants’ needs, allowing them to control media and recognize if a cell phone is left in the car, and in the case of an accident, adapt airbags to the occupants’ body shape and position