A real-time gesture recognition system using near-infrared imagery

Tomás Mantecón, Carlos R del-Blanco, Fernando Jaureguizar and Narciso García

PLOS ONE, 2019, vol. 14, issue 10, 1-17

Abstract: Visual hand gesture recognition systems are promising technologies for Human Computer Interaction, as they allow a more immersive and intuitive interaction. Most of these systems are based on the analysis of skeleton information, which is in turn inferred from color, depth, or near-infrared imagery. However, the robust extraction of skeleton information from images is only possible for a subset of hand poses, which restricts the range of gestures that can be recognized. In this paper, a real-time hand gesture recognition system based on a near-infrared device is presented, which directly analyzes the infrared imagery to infer static and dynamic gestures, without using skeleton information. Thus, a much wider range of hand gestures can be recognized in comparison with skeleton-based approaches. To validate the proposed system, a new dataset of near-infrared imagery has been created, from which good results that outperform other state-of-the-art strategies have been obtained.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0223320

DOI: 10.1371/journal.pone.0223320

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