Are mid-air dynamic gestures applicable to user identification?

Liu, Heng and Dai, Liangliang and Hou, Shudong and Han, Jungong and Liu, Hongshen (2018) Are mid-air dynamic gestures applicable to user identification? Pattern Recognition Letters. ISSN 0167-8655

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Abstract

Abstract Unlike the existing gesture related research predominantly focusing on gesture recognition (classification), this work explores the feasibility and the potential of mid-air dynamic gesture based user identification through presenting an efficient bidirectional GRU (Gated Recurrent Unit) network. From the perspective of the feature analysis from the Bi-GRU network used for different recognition tasks, we make a detailed investigation on the correlation and the difference between the gesture type features and the gesture user identity characteristics. During this process, two unsupervised feature representation methods – PCA and hash ITQ (Iterative Quantization) are fully used to perform feature reduction and feature binary coding. Experiments and analysis based on our dynamic gesture data set (60 individuals) exemplify the effectiveness of the proposed mid-air dynamic gesture based user identification approach and clearly reveal the relationship between the gesture type features and the gesture user identity characteristics.

Item Type:
Journal Article
Journal or Publication Title:
Pattern Recognition Letters
Additional Information:
This is the author’s version of a work that was accepted for publication in Physics Reports. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Physics Reports, 373, 4-5, 2003 DOI: 10.1016/S0370-1573(02)00269-7
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/1700/1707
Subjects:
?? GESTURE BASED USER IDENTIFICATIONGESTURE USER IDENTITY CHARACTERISTICSBI-GRUMID-AIR DYNAMIC GESTURESARTIFICIAL INTELLIGENCESIGNAL PROCESSINGSOFTWARECOMPUTER VISION AND PATTERN RECOGNITION ??
ID Code:
124862
Deposited By:
Deposited On:
24 Apr 2018 14:56
Refereed?:
Yes
Published?:
Published
Last Modified:
17 Sep 2023 02:16