Abstract
Background
Scene supervision is a major tool to make medical robots safer and more intuitive. The paper shows an approach to efficiently use 3D cameras within the surgical operating room to enable for safe human robot interaction and action perception. Additionally the presented approach aims to make 3D camera-based scene supervision more reliable and accurate.
Methods
A camera system composed of multiple Kinect and time-of-flight cameras has been designed, implemented and calibrated. Calibration and object detection as well as people tracking methods have been designed and evaluated.
Results
The camera system shows a good registration accuracy of 0.05 m. The tracking of humans is reliable and accurate and has been evaluated in an experimental setup using operating clothing. The robot detection shows an error of around 0.04 m.
Conclusions
The robustness and accuracy of the approach allow for an integration into modern operating room. The data output can be used directly for situation and workflow detection as well as collision avoidance.
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Acknowledgments
This research was funded by the European Commissions Seventh Framework program within the projects Patient Safety in Robotic Surgery (SAFROS) under Grant No. 248960 and Active Constraints Technologies for Ill-defined or Volatile Environments (ACTIVE) under Grant No. 270460. The authors thank the EU for its financial support. The authors thank NVIDIA (USA) for providing two NVIDIA Geforce GTX Titan graphic adapters for the research shown in this paper.
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Beyl, T., Nicolai, P., Comparetti, M.D. et al. Time-of-flight-assisted Kinect camera-based people detection for intuitive human robot cooperation in the surgical operating room. Int J CARS 11, 1329–1345 (2016). https://doi.org/10.1007/s11548-015-1318-7
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DOI: https://doi.org/10.1007/s11548-015-1318-7