Upper Bounds for Localization Errors in 2D Human Pose Estimation
Patrick Schlosser,Christoph Ledermann,Tamim Asfour,Patrick Schlosser,Christoph Ledermann,Tamim Asfour
Obtaining reliable detections of a human is crucial for many safety-related robotic tasks. This can be done by human pose estimation methods, which predict the position of several different keypoints of the human body. In most cases, recent approaches based on neural networks produce ‘good’ results, i.e. predictions with small localization errors, however, large errors do also occur. For an indivi...
