Design of embedded gesture recognition system for robotic applications

Ainur Begalinova, Almas Shintemirov

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

1 Citation (Scopus)

Abstract

Recent developments of system-on-chip (SOC) technologies have found a lot of applications in robotic embedded system design. Powerful miniature SOC boards allow development of mobile robots with advanced onboard computation performance executing complex data processing and control algorithms. This paper presents a preliminary results of an embedded system design of a mobile robot platform implementing gesture recognition and control. The system is designed using a BeagleBoard-xM SOC board and an Asus Xtion Live 3D camera. System implementation and analysis of a human hand detection and tracking from depth images are discussed.

Original languageEnglish
Title of host publication8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479941209
DOIs
Publication statusPublished - 2014
Event8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Astana, Kazakhstan
Duration: Oct 15 2014Oct 17 2014

Other

Other8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014
CountryKazakhstan
CityAstana
Period10/15/1410/17/14

Fingerprint

Gesture recognition
Robotics
Embedded systems
Mobile robots
Systems analysis
Cameras
System-on-chip

Keywords

  • Asus Xtion Live depth camera
  • BeagleBoard-xM
  • Embedded system
  • Hand gesture recognition
  • Hand tracking

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications

Cite this

Begalinova, A., & Shintemirov, A. (2014). Design of embedded gesture recognition system for robotic applications. In 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings [7035931] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAICT.2014.7035931

Design of embedded gesture recognition system for robotic applications. / Begalinova, Ainur; Shintemirov, Almas.

8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014. 7035931.

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

Begalinova, A & Shintemirov, A 2014, Design of embedded gesture recognition system for robotic applications. in 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings., 7035931, Institute of Electrical and Electronics Engineers Inc., 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014, Astana, Kazakhstan, 10/15/14. https://doi.org/10.1109/ICAICT.2014.7035931
Begalinova A, Shintemirov A. Design of embedded gesture recognition system for robotic applications. In 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc. 2014. 7035931 https://doi.org/10.1109/ICAICT.2014.7035931
Begalinova, Ainur ; Shintemirov, Almas. / Design of embedded gesture recognition system for robotic applications. 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2014.
@inproceedings{8e97f9551985416395469bf625e04a43,
title = "Design of embedded gesture recognition system for robotic applications",
abstract = "Recent developments of system-on-chip (SOC) technologies have found a lot of applications in robotic embedded system design. Powerful miniature SOC boards allow development of mobile robots with advanced onboard computation performance executing complex data processing and control algorithms. This paper presents a preliminary results of an embedded system design of a mobile robot platform implementing gesture recognition and control. The system is designed using a BeagleBoard-xM SOC board and an Asus Xtion Live 3D camera. System implementation and analysis of a human hand detection and tracking from depth images are discussed.",
keywords = "Asus Xtion Live depth camera, BeagleBoard-xM, Embedded system, Hand gesture recognition, Hand tracking",
author = "Ainur Begalinova and Almas Shintemirov",
year = "2014",
doi = "10.1109/ICAICT.2014.7035931",
language = "English",
booktitle = "8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
address = "United States",

}

TY - GEN

T1 - Design of embedded gesture recognition system for robotic applications

AU - Begalinova, Ainur

AU - Shintemirov, Almas

PY - 2014

Y1 - 2014

N2 - Recent developments of system-on-chip (SOC) technologies have found a lot of applications in robotic embedded system design. Powerful miniature SOC boards allow development of mobile robots with advanced onboard computation performance executing complex data processing and control algorithms. This paper presents a preliminary results of an embedded system design of a mobile robot platform implementing gesture recognition and control. The system is designed using a BeagleBoard-xM SOC board and an Asus Xtion Live 3D camera. System implementation and analysis of a human hand detection and tracking from depth images are discussed.

AB - Recent developments of system-on-chip (SOC) technologies have found a lot of applications in robotic embedded system design. Powerful miniature SOC boards allow development of mobile robots with advanced onboard computation performance executing complex data processing and control algorithms. This paper presents a preliminary results of an embedded system design of a mobile robot platform implementing gesture recognition and control. The system is designed using a BeagleBoard-xM SOC board and an Asus Xtion Live 3D camera. System implementation and analysis of a human hand detection and tracking from depth images are discussed.

KW - Asus Xtion Live depth camera

KW - BeagleBoard-xM

KW - Embedded system

KW - Hand gesture recognition

KW - Hand tracking

UR - http://www.scopus.com/inward/record.url?scp=84988273436&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84988273436&partnerID=8YFLogxK

U2 - 10.1109/ICAICT.2014.7035931

DO - 10.1109/ICAICT.2014.7035931

M3 - Conference contribution

BT - 8th IEEE International Conference on Application of Information and Communication Technologies, AICT 2014 - Conference Proceedings

PB - Institute of Electrical and Electronics Engineers Inc.

ER -