Skip to main content

Individual Identification from 3D Captured Movement Data

Buy Article:

$113.00 plus tax (Refund Policy)

Abstract:

3D motion capture data can now be obtained from human body directly. They reflect the real motion of human beings. In this paper, against traditional 2D recognition methods, we propose a novel method for human motion identification from 3D motion captured data. We take a data-driven modeling approach to learn characteristics from a marker-based training set. Principal Components Analysis (PCA) is used to get the low-dimension features from a captured movement sequence. A similarity computing technique is used to compute the distance of different motion clips. The method is tested on motion clips from the CMU motion capture database. All the motions can be identified from the motion clips. The results demonstrate that our method has good identification abilities. Moreover, for periodical motions, the identification results are nearly irrespectively with the length of captured sequence.

Keywords: DEGREE OF FREEDOM; INDIVIDUAL IDENTIFICATION; MOTION ANALYSIS; MOTION CAPTURE; PRINCIPAL COMPONENT ANALYSIS

Document Type: Research Article

DOI: http://dx.doi.org/10.1166/sl.2012.1855

Publication date: January 1, 2012

More about this publication?
  • The growing interest and activity in the field of sensor technologies requires a forum for rapid dissemination of important results: Sensor Letters is that forum. Sensor Letters offers scientists, engineers and medical experts timely, peer-reviewed research on sensor science and technology of the highest quality. Sensor Letters publish original rapid communications, full papers and timely state-of-the-art reviews encompassing the fundamental and applied research on sensor science and technology in all fields of science, engineering, and medicine. Highest priority will be given to short communications reporting important new scientific and technological findings.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • Ingenta Connect is not responsible for the content or availability of external websites
asp/senlet/2012/00000010/F0020001/art00050
dcterms_title,dcterms_description,pub_keyword
6
5
20
40
5

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more