Localization of skin features on the hand and wrist from small image patches

Lee Stearns, Uran Oh, Bridget J. Cheng, Leah Findlater, David Ross, Rama Chellappa, Jon E. Froehlich

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations


Skin-based biometrics rely on the distinctiveness of skin patterns across individuals for identification. In this paper, we investigate whether small image patches of the skin can be localized on a user's body, determining not 'who?' instead 'where?' Applying techniques from biometrics and computer vision, we introduce a hierarchical classifier that estimates a location from the image texture and refines the estimate with keypoint matching and geometric verification. To evaluate our approach, we collected 10,198 close-up images of 17 hand and wrist locations across 30 participants. Within-person algorithmic experiments demonstrate that an individual's own skin features can be used to localize their skin surface image patches with an F1 score of 96.5%. As secondary analyses, we assess the effects of training set size and between-person classification. We close with a discussion of the strengths and limitations of our approach and evaluation methods as well as implications for future applications using a wearable camera to support touch-based, location-specific taps and gestures on the surface of the skin.

Original languageEnglish
Title of host publication2016 23rd International Conference on Pattern Recognition, ICPR 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781509048472
StatePublished - 1 Jan 2016
Event23rd International Conference on Pattern Recognition, ICPR 2016 - Cancun, Mexico
Duration: 4 Dec 20168 Dec 2016

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651


Conference23rd International Conference on Pattern Recognition, ICPR 2016

Bibliographical note

Publisher Copyright:
© 2016 IEEE.


  • Biometrics and computer vision applications
  • On-body input
  • Skin texture classification


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