XIa, Baiqiang and Dahyot, Rozenn and Ruttle, Jonathan and Caulfield, Darren and Lacey, Gerard (2015) Hand Hygiene Poses Recognition with RGB-D Videos. Proceedings of the 17th Irish Machine Vision and Image Processing conference. pp. 43-50.

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Abstract

Hand hygiene is the most effective way in preventing the health care-associated infection. In this work, we propose to investigate the automatic recognition of the hand hygiene poses with RGB-D videos. Different classifiers are experimented with the Histogram of Oriented Gradient (HOG) features extracted from the hand regions. With a frame-level classification rate of more than 95%, and with 100% video-level classification rate, we demonstrate the effectiveness of our method for recognizing these hand hygiene poses. Also, we demonstrate that using the temporal information, and combining the color with depth information can improve the recognition accuracy.

Item Type:	Article
Keywords:	Hand Hygiene; Poses Recognition; RGB-D;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	15260
Depositing User:	Rozenn Dahyot
Date Deposited:	18 Jan 2022 12:11
Journal or Publication Title:	Proceedings of the 17th Irish Machine Vision and Image Processing conference
Publisher:	Irish Pattern Recognition & Classification Society
Refereed:	Yes
URI:	Organisation
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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