Login / Signup

Accuracy Assessment of Joint Angles Estimated from 2D and 3D Camera Measurements.

Izaak Van CrombruggeSeppe SelsBart RibbensGunther SteenackersRudi PenneSteve Vanlanduit
Published in: Sensors (Basel, Switzerland) (2022)
To automatically evaluate the ergonomics of workers, 3D skeletons are needed. Most ergonomic assessment methods, like REBA, are based on the different 3D joint angles. Thanks to the huge amount of training data, 2D skeleton detectors have become very accurate. In this work, we test three methods to calculate 3D skeletons from 2D detections: using the depth from a single RealSense range camera, triangulating the joints using multiple cameras, and combining the triangulation of multiple camera pairs. We tested the methods using recordings of a person doing different assembly tasks. We compared the resulting joint angles to the ground truth of a VICON marker-based tracking system. The resulting RMS angle error for the triangulation methods is between 12° and 16°, showing that they are accurate enough to calculate a useful ergonomic score from.
Keyphrases
  • high resolution
  • high speed
  • convolutional neural network
  • working memory
  • machine learning
  • optical coherence tomography
  • electronic health record
  • deep learning