This paper presents a framework allowing emblematic gestures detection, segmentation and their recognition for human-robots interaction purposes. This framework is based on a new coding of arms’ kinematics reflecting both the muscular activity of the performer and the appearance of arm seen by the recipient when a gesture is performed. Following that, gestures can be seen as sequences of torques activations leading arm’s parts to express a comprehensive meaning. In addition, these sequences have very stable topologies and shapes regardless to performers. This facilitates the generalization of the recognition process with a minimalistic learning effort for online usages. Promising results were obtained for a set of 5 classes of gestures performed by 19 different persons.
Emblematic Gestures Recognition
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Chellali, R, & Renna, I. "Emblematic Gestures Recognition." Proceedings of the ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis. Volume 2: Applied Fluid Mechanics; Electromechanical Systems and Mechatronics; Advanced Energy Systems; Thermal Engineering; Human Factors and Cognitive Engineering. Nantes, France. July 2–4, 2012. pp. 755-761. ASME. https://doi.org/10.1115/ESDA2012-82481
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