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Research at St Andrews

Opisthenar: hand poses and finger tapping recognition by observing back of hand using embedded wrist camera

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Author(s)

Hui Shyong Yeo, Erwin Wu, Juyoung Lee, Aaron John Quigley, Hideki Koike

School/Research organisations

Abstract

We introduce a vision-based technique to recognize static hand poses and dynamic finger tapping gestures. Our approach employs a camera on the wrist, with a view of the opisthenar (back of the hand) area. We envisage such cameras being included in a wrist-worn device such as a smartwatch, fitness tracker or wristband. Indeed, selected off-the-shelf smartwatches now incorporate a built-in camera on the side for photography purposes. However, in this configuration, the fingers are occluded from the view of the camera. The oblique angle and placement of the camera make typical vision-based techniques difficult to adopt. Our alternative approach observes small movements and changes in the shape, tendons, skin and bones on the opisthenar area. We train deep neural networks to recognize both hand poses and dynamic finger tapping gestures. While this is a challenging configuration for sensing, we tested the recognition with a real-time user test and achieved a high recognition rate of 89.4% (static poses) and 67.5% (dynamic gestures). Our results further demonstrate that our approach can generalize across sessions and to new users. Namely, users can remove and replace the wrist-worn device while new users can employ a previously trained system, to a certain degree. We conclude by demonstrating three applications and suggest future avenues of work based on sensing the back of the hand.
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Details

Original languageEnglish
Title of host publicationProceedings of the 32nd Annual ACM Symposium on User Interface Software and Technology (UIST 2019)
Place of PublicationNew York
PublisherACM
Pages963-971
Number of pages9
ISBN (Electronic)9781450368162
DOIs
Publication statusPublished - 17 Oct 2019
Event32nd ACM User Interface Software and Technology Symposium (UIST 2019) - New Orleans, United States
Duration: 20 Oct 201923 Oct 2019
Conference number: 32
http://uist.acm.org/uist2019/

Conference

Conference32nd ACM User Interface Software and Technology Symposium (UIST 2019)
Abbreviated titleUIST 2019
CountryUnited States
CityNew Orleans
Period20/10/1923/10/19
Internet address

    Research areas

  • Back of the hand, Opisthenar, Hand pose, Finger tapping

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