FMHash: Deep Hashing of In-Air-Handwriting for User Identification

Duo Lu, DIjiang Huang, Anshul Rai

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

Abstract

Many mobile systems and wearable devices, such as Virtual Reality (VR) or Augmented Reality (AR) headsets, lack a keyboard or touchscreen to type an ID and password for signing into a virtual website. However, they are usually equipped with gesture capture interfaces to allow the user to interact with the system directly with hand gestures. Although gesture-based authentication has been well-studied, less attention is paid to the gesture-based user identification problem, which is essentially an input method of account ID and an efficient searching and indexing method of a database of gesture signals. In this paper, we propose FMHash (i.e., Finger Motion Hash), a user identification framework that can generate a compact binary hash code from a piece of in-air-handwriting of an ID string. This hash code enables indexing and fast search of a large account database using the in-air-handwriting by a hash table. To demonstrate the effectiveness of the framework, we implemented a prototype and achieved 99.5% precision and 92.6% recall with exact hash code match on a dataset of 200 accounts collected by us. The ability of hashing in-air-handwriting pattern to binary code can be used to achieve convenient sign-in and sign-up with in-air-handwriting gesture ID on future mobile and wearable systems connected to the Internet.

Original languageEnglish (US)
Title of host publication2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680889
DOIs
StatePublished - May 1 2019
Event2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
Duration: May 20 2019May 24 2019

Publication series

NameIEEE International Conference on Communications
Volume2019-May
ISSN (Print)1550-3607

Conference

Conference2019 IEEE International Conference on Communications, ICC 2019
CountryChina
CityShanghai
Period5/20/195/24/19

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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  • Cite this

    Lu, D., Huang, DI., & Rai, A. (2019). FMHash: Deep Hashing of In-Air-Handwriting for User Identification. In 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings [8761508] (IEEE International Conference on Communications; Vol. 2019-May). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICC.2019.8761508