One-shot gesture recognition with attention-based DTW for human-robot collaboration

One-shot gesture recognition with attention-based DTW for human-robot collaboration PurposeThis paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems.Design/methodology/approachThis paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture.FindingsThe proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly.Originality/valueAccording to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Assembly Automation Emerald Publishing

One-shot gesture recognition with attention-based DTW for human-robot collaboration

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Publisher
Emerald Publishing
Copyright
Copyright © Emerald Group Publishing Limited
ISSN
0144-5154
DOI
10.1108/AA-11-2018-0228
Publisher site
See Article on Publisher Site

Abstract

PurposeThis paper aims to present a one-shot gesture recognition approach which can be a high-efficient communication channel in human–robot collaboration systems.Design/methodology/approachThis paper applies dynamic time warping (DTW) to align two gesture sequences in temporal domain with a novel frame-wise distance measure which matches local features in spatial domain. Furthermore, a novel and robust bidirectional attention region extraction method is proposed to retain information in both movement and hold phase of a gesture.FindingsThe proposed approach is capable of providing efficient one-shot gesture recognition without elaborately designed features. The experiments on a social robot (JiaJia) demonstrate that the proposed approach can be used in a human–robot collaboration system flexibly.Originality/valueAccording to previous literature, there are no similar solutions that can achieve an efficient gesture recognition with simple local feature descriptor and combine the advantages of local features with DTW.

Journal

Assembly AutomationEmerald Publishing

Published: Aug 2, 2019

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