Unsupervised Gesture Segmentation by Motion Detection of a Real-Time Data Stream

• Published in: IEEE transactions on industrial informatics Vol. 13; no. 2; pp. 473 - 481
• Main Authors: Simao, Miguel A., Neto, Pedro, Gibaru, Olivier
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.04.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Data transmission; Genetic algorithms; Gesture recognition; Gestures; human–machine interaction (HMI); Inversions; motion; Motion perception; Motion segmentation; Real time; Real-time systems; robotics; Segmentation; Service robots; Training; unsupervised
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2016.2613683

Continuous and real-time gesture spotting is a key factor in the development of novel human-machine interaction modalities. Gesture recognition can be greatly improved with previous reliable segmentation. This paper introduces a new unsupervised threshold-based hand/arm gesture segmentation method t...