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Study on ensemble between humans and robots Consideration on Einsatz detection method

Kazuteru TOBITA, Ryusuke Ishikawa, Kazuhiro Mima

Year
2022
Citations
2

Abstract

We are studying human and robot ensembles as a highly collaborative work. In this report, we considered the tracking method and the detection method of the performance start point (Einsatz), and obtained the following conclusions. By comparing tracking by cascade, KCF, MIL, and MediaPipe, it was shown that skeleton detection by MediaPipe is desirable comprehensively from the frame rate, tracking stability, and the large number of feature points. In Einsatz detection using MediaPipe and MLP classifier, the optimum parameters were extracted by performing a grid search.

Keywords

Artificial intelligenceComputer scienceCascading classifiersClassifier (UML)Pattern recognition (psychology)RobotGridFrame (networking)Computer visionTracking (education)

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