We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Corrective Self Defence Training Unit using sensing of Kinect Maps

by Mayank Vij, Suma Dawn
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 89 - Number 10
Year of Publication: 2014
Authors: Mayank Vij, Suma Dawn
10.5120/15665-3692

Mayank Vij, Suma Dawn . Corrective Self Defence Training Unit using sensing of Kinect Maps. International Journal of Computer Applications. 89, 10 ( March 2014), 8-11. DOI=10.5120/15665-3692

@article{ 10.5120/15665-3692,
author = { Mayank Vij, Suma Dawn },
title = { Corrective Self Defence Training Unit using sensing of Kinect Maps },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 89 },
number = { 10 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 8-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume89/number10/15665-3692/ },
doi = { 10.5120/15665-3692 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:08:51.263793+05:30
%A Mayank Vij
%A Suma Dawn
%T Corrective Self Defence Training Unit using sensing of Kinect Maps
%J International Journal of Computer Applications
%@ 0975-8887
%V 89
%N 10
%P 8-11
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In the sports fields and technology, the accuracy of an athlete can never be monitored with 100% accuracy with naked eyes. Moves that are done by an athlete or a sports person in the game such as his stride length and the stride frequency cannot be easily seen by a person and hence, detection and correction of the minute mistakes that are being made are overlooked. For instance, while doing push-ups a person's head, neck, waist and ankle should be in a single straight line. In this paper, we discuss a sports training system which uses Microsoft Kinect for motion sensing. The infrared depth stream translates the presence of a user in real world, into digital space by tracking his/her joint coordinates. As per our empirical studies, Kinect maps the x,y and z coordinates of 20 primary joints of the body. This data forms the basis of our calculations as elaborated in the literature. This work gives a basis of how movements and postures may be corrected by the use of sensors like Kinect in an effective and efficient manner.

References
  1. Abhishek Kar. " Skeletal Tracking using Microsoft Kinect", Department of Computer Science and Engineering, IIT Kanpur.
  2. "Real time Human pose recognition in parts from Single depth image", Microsoft Research Cambridge & Xbox Incubation.
  3. T. Roberts. "Natural Full Body Interaction for Navigation in Dismounted Soldier Training",in Interservice/Industry Training, Simulation, and Education Conference 2011.
  4. Takayuki Nakamura," Real-time 3-D Object Tracking Using Kinect Sensor",in 2011 IEEE International Conference on Robotics and Biomimetics December 7-11, 2011, Phuket, Thailand.
  5. A. Poolton. " Conducting a Comparative Study of Traditional and Hybrid Xbox Control Systems within a Developed Game", NCCA, Bournemouth University,2011.
  6. "Army Trends Towards Blended Training",I/ITSEC Showdaily,November 2011
  7. Navid Zolghadr zolghadr and Csaba Szepesv . "An adaptive algorithm for Finite stochastic particle monitoring",in Department of Computing Science, University of Alberta, AB, Canada .
  8. Antonio Ricciardi and Patrick Thill , "Adaptive AI for Fighting Games",Stanford University 2008.
  9. Niemeyer,G. , PING: Poetic Charge and Technical Implementation, The MIT Press,2005 from http://www. jstor. org/stable/20206073
  10. Allen,R. ,The Emergence Project: "The British Soul", The MIT Press,2005 from http://www. jstor. org/stable/20206074
  11. Wikipedia, Natural User Interface, from http://en. wikipedia. org/wiki/Natural_user_interface
  12. Wikipedia, Control Flow Graph, from http://en. wikipedia. org/wiki/Control_flow_graph.
Index Terms

Computer Science
Information Sciences

Keywords

Kinect Motion Sensing Sports Training Sports Training Gestures HMM.