Feature Selection for Hand Gesture Recognition in Human-Robot Interaction

Matthew McCarver, Jing Qin, Biyun Xie

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

Abstract

Hand gesture recognition has been playing an important role in robotic applications, which allows robots to communicate with humans in an effective way. However, it typically desires to process high-dimensional data, such as images or sensor measurements. To address the computational challenges due to the data growth, it is desirable to select most relevant features during recognition by reducing the redundancy of the data. In this paper, we propose a novel feature selection approach based on the separable nonnegative matrix factorization (NMF) framework for hand gesture recognition. In particular, we adopt a nonconvex regularization term, i.e., the ratio of matrix nuclear norm and Frobenius norm. The proposed method reduces the data dimension by utilizing the data low-rankness in an adaptive way. To address the nonconvexity of the proposed model, we reformulate it by introducing an auxiliary variable and then apply the alternating direction method of multipliers (ADMM). Furthermore, a variety of numerical experiments on binary and grayscale hand gesture images demonstrate the efficiency of the proposed feature selection approach in improving the quality of factorization and its potential impact on robotic applications.

Original languageEnglish
Title of host publication33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024
Pages1222-1227
Number of pages6
ISBN (Electronic)9798350375022
DOIs
StatePublished - 2024
Event33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024 - Pasadena, United States
Duration: Aug 26 2024Aug 30 2024

Publication series

NameIEEE International Workshop on Robot and Human Communication, RO-MAN
ISSN (Print)1944-9445
ISSN (Electronic)1944-9437

Conference

Conference33rd IEEE International Conference on Robot and Human Interactive Communication, ROMAN 2024
Country/TerritoryUnited States
CityPasadena
Period8/26/248/30/24

Bibliographical note

Publisher Copyright:
© 2024 IEEE.

Keywords

  • feature
  • hand gesture recognition
  • low-rank
  • nonnegative matrix factorization
  • robot

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Human-Computer Interaction
  • Software

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