Next Article in Journal
An Outlook on Physical and Virtual Sensors for a Socially Interactive Internet
Next Article in Special Issue
Lightweight Visual Odometry for Autonomous Mobile Robots
Previous Article in Journal
General Signal Model for Multiple-Input Multiple-Output GMTI Radar
Previous Article in Special Issue
Fast Visual Odometry for a Low-Cost Underwater Embedded Stereo System
Article Menu
Issue 8 (August) cover image

Export Article

Open AccessArticle
Sensors 2018, 18(8), 2577;

Handshape Recognition Using Skeletal Data

Department of Computer and Control Engineering, Rzeszow University of Technology, 35-959 Rzeszow, Poland
Author to whom correspondence should be addressed.
Received: 10 July 2018 / Revised: 2 August 2018 / Accepted: 5 August 2018 / Published: 6 August 2018
(This article belongs to the Special Issue Visual Sensors)
Full-Text   |   PDF [11756 KB, uploaded 8 August 2018]   |  


In this paper, a method of handshapes recognition based on skeletal data is described. A new feature vector is proposed. It encodes the relative differences between vectors associated with the pointing directions of the particular fingers and the palm normal. Different classifiers are tested on the demanding dataset, containing 48 handshapes performed 500 times by five users. Two different sensor configurations and significant variation in the hand rotation are considered. The late fusion at the decision level of individual models, as well as a comparative study carried out on a publicly available dataset, are also included. View Full-Text
Keywords: handshape recognition; sign language; finger alphabet; skeletal data handshape recognition; sign language; finger alphabet; skeletal data

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Kapuscinski, T.; Organisciak, P. Handshape Recognition Using Skeletal Data. Sensors 2018, 18, 2577.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top