CFP last date
20 November 2024
Call for Paper
December Edition
IJCA solicits high quality original research papers for the upcoming December edition of the journal. The last date of research paper submission is 20 November 2024

Submit your paper
Know more
Reseach Article

3D Accelerometer based Gesture Device for the Recognition of Digits

by Himani Arora
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 115 - Number 15
Year of Publication: 2015
Authors: Himani Arora
10.5120/20230-2528

Himani Arora . 3D Accelerometer based Gesture Device for the Recognition of Digits. International Journal of Computer Applications. 115, 15 ( April 2015), 30-35. DOI=10.5120/20230-2528

@article{ 10.5120/20230-2528,
author = { Himani Arora },
title = { 3D Accelerometer based Gesture Device for the Recognition of Digits },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 115 },
number = { 15 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume115/number15/20230-2528/ },
doi = { 10.5120/20230-2528 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:54:56.792487+05:30
%A Himani Arora
%T 3D Accelerometer based Gesture Device for the Recognition of Digits
%J International Journal of Computer Applications
%@ 0975-8887
%V 115
%N 15
%P 30-35
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Gesture recognition helps in the development of a more natural and intuitive human computer interaction. It has several applications in virtual reality and can be used to control robots as well as home appliances. In this paper, the design and working of a compact handheld device that works with a computer to recognize hand gestures has been presented. A single 3-D accelerometer has been used for sensing the motion and Support Vector Machine has been employed for recognizing the gesture. The data processing has been implemented in MATLAB and a graphical user interface has also been developed to make the application user friendly. All digits from 0-9 have been recognized with a high accuracy for both user dependent and independent gesture recognition. In contrast to the previous models for digit recognition, a simpler approach that uses frame based temporal features has been presented to give a high recognition rate. .

References
  1. H. K. Kaura, V. Honrao, S. Patil, and P. Shetty, "Gesture Controlled Robot using Image Processing," Int. J. Adv. Res. Artif. Intell. , vol. 2, no. 5, pp. 69–77, 2013.
  2. V. S. Kulkarni and S. . Lokhande, "Appearance Based Recognition of American Sign Language Using Gesture Segmentation," Int. J. Comput. Sci. Eng. , vol. 02, no. 03, pp. 560–565, 2010.
  3. A. S. Ghotkar and G. K. Kharate, "Vision based Real Time Hand Gesture Recognition Techniques for Human Computer Interaction," Int. J. Comput. Appl. , vol. 70, no. 16, pp. 1–6, 2013.
  4. R. B. Dan and P. S. Mohod, "Survey on Hand Gesture Recognition Approaches," Int. J. Comput. Sci. Inf. Technol. , vol. 5, no. 2, pp. 2050–2052, 2014.
  5. P. Kumar, J. Verma, and S. Prasad, "Hand Data Glove : A Wearable Real-Time Device for Human- Computer Interaction," Int. J. Adv. Sci. Technol. , vol. 43, pp. 15–26, 2012.
  6. E. Morganti, L. Angelini, A. Adami, D. Lalanne, L. Lorenzelli, and E. Mugellini, "A Smart Watch with Embedded Sensors to Recognize Objects, Grasps and Forearm Gestures," Procedia Eng. , vol. 41, pp. 1169–1175, 2012.
  7. J. Wu, G. Pan, D. Zhang, G. Qi, and S. Li, "Gesture Recognition with a 3-D Accelerometer," in 6th International Conference on Ubiquitous Intelligence and Computing (UIC '09), 2009, pp. 25–38.
  8. T. Schl, B. Poppinga, N. Henze, and S. Boll, "Gesture Recognition with a Wii Controller," in 2nd international conference on Tangible and embedded interaction (TEI '08), 2008, pp. 1–4.
  9. B. M. Lee-Cosio, C. Delgado-Mata, and J. Ibanez, "ANN for Gesture Recognition using Accelerometer Data," Procedia Technol. , vol. 3, pp. 109–120, 2012.
  10. J. Liu, Z. Pan, and L. Xiangcheng, "An accelerometer-based gesture recognition algorithm and its application for 3D interaction," Comput. Sci. Inf. Syst. , vol. 7, no. 1, pp. 177–188, 2010.
  11. K. J. Patil, A. H. Karode, and S. R. Suralkar, "Gesture Recognition of Handwritten Digit using Accelerometer based Digital Pen," Int. J. Appl. or Innov. Eng. Manag. , vol. 3, no. 4, pp. 353–357, 2014.
  12. R. Xu, S. Zhou, and W. J. Li, "MEMS Accelerometer Based Nonspecific-User Hand Gesture Recognition," IEEE Sens. J. , vol. 12, no. 5, pp. 1166–1173, 2012.
  13. J. Liu, L. Zhong, J. Wickramasuriya, and V. Vasudevan, "uWave: Accelerometer-based personalized gesture recognition and its applications," Pervasive Mob. Comput. , vol. 5, no. 6, pp. 657–675, Dec. 2009.
  14. Chang, C. & Lin, C. (2011). LIBSVM : a library for support vector machines. ACM Transactions on Intelligent Systems and Technology. Software available at http://www. csie. ntu. edu. tw/~cjlin/libsvm
  15. C. Hsu, C. Chang, and C. Lin, "A Practical Guide to Support Vector Classification," pp. 1–16, 2010.
  16. D. Figo, P. C. Diniz, D. R. Ferreira, and M. P. Cardoso, "Preprocessing Techniques for Context Recognition from Accelerometer Data," Pers. Ubiquitous Comput. , vol. 14, no. 7, pp. 645–662, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Human Computer Interaction Digit recognition