  The rapid growth of collaborative robotics in production requires new
automation technologies that take human and machine equally into account. In
this work, we describe a monocular camera based system to detect human-machine
interactions from a bird's-eye perspective. Our system predicts poses of humans
and robots from a single wide-angle color image. Even though our approach works
on 2D color input, we lift the majority of detections to a metric 3D space. Our
system merges pose information with predefined virtual sensors to coordinate
human-machine interactions. We demonstrate the advantages of our system in
three use cases.
