Coherence in One-Shot Gesture Recognition for Human-Robot Interaction
María Eugenia Cabrera, Richard M. Voyles, Juan Pablo Wachs · 2018
An experiment was conducted where a robotic platform performs artificially generated gestures and both trained classifiers and human participants recognize. Classification accuracy is evaluated through a new metric of coherence in gesture recognition between humans and robots. Experimental results showed an average recognition performance of 89.2% for the trained classifiers and 92.5% for the participants. Coherence in one-shot gesture recognition was determined to be gamma = 93.8%. This new metric provides a quantifier for validating how realistic the robotic generated gestures are.