skip to main content

Search for: All records

Creators/Authors contains: "Duo Lu, Linzhen Luo"

Note: When clicking on a Digital Object Identifier (DOI) number, you will be taken to an external site maintained by the publisher. Some full text articles may not yet be available without a charge during the embargo (administrative interval).
What is a DOI Number?

Some links on this page may take you to non-federal websites. Their policies may differ from this site.

  1. Hand-gesture and in-air-handwriting provide ways for users to input information in Augmented Reality (AR) and Virtual Reality (VR) applications where a physical keyboard or a touch screen is unavailable. However, understanding the movement of hands and fingers is challenging, which requires a large amount of data and data-driven models. In this paper, we propose an open research infrastructure named FMKit for in-air-handwriting analysis, which contains a set of Python libraries and a data repository collected from over 180 users with two different types of motion capture sensors. We also present three research tasks enabled by FMKit, including in-air-handwriting based user authentication, user identification, and word recognition, and preliminary baseline performance.
  2. Hand-gesture and in-air-handwriting provide ways for users to input information in Augmented Reality (AR) and Virtual Reality (VR) applications where a physical keyboard or a touch screen is unavailable. However, understanding the movement of hands and fingers is challenging, which requires a large amount of data and data-driven models. In this paper, we propose an open research infrastructure named FMKit for in-air-handwriting analysis, which contains a set of Python libraries and a data repository collected from over 180 users with two different types of motion capture sensors. We also present three research tasks enabled by FMKit, including in-air-handwriting based user authentication, user identification, and word recognition, and preliminary baseline performance.