Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

Accelerometer-based gait recognition via voting by signature points

Accelerometer-based gait recognition via voting by signature points

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
Electronics Letters — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

A novel algorithm to recognise human identities via gait by body-worn accelerometers is presented. It uses acceleration information to measure human gait dynamics. Acceleration-based gait recognition is a non-intrusive biometric measurement, which is insensitive to changes of lighting conditions and viewpoint. The proposed algorithm first extracts signature points from gait acceleration signals, and then identifies the gait pattern using a signature point-based voting scheme. Experiments with a data set of 30 subjects show that the proposed algorithm significantly outperforms other existing methods and achieves a high recognition rate of 96.7% for the case of five accelerometers.

References

    1. 1)
      • Lowe, D.: `Object recognition from local scale-invariant features', IEEE Int. Conf. on Computer Vision (ICCV'99), 1999, 2.
    2. 2)
      • Mantyjarvi, J., Lindholm, M., Vildjiounaite, E., Makela, S., Ailisto, H., Electron, V., Oulu, F.: `Identifying users of portable devices from gait pattern with accelerometers', IEEE Int. Conf. on Acoustics, Speech, and Signal Processing (ICASSP'05), 2005, 2.
    3. 3)
      • Gafurov, D., Snekkenes, E., Bours, P.: `Gait authentication and identification using wearable accelerometer sensor', IEEE Workshop on Automatic Identification Advanced Technologies, 2007, p. 220–225.
    4. 4)
      • Bao, L., Intille, S.: `Activity recognition from user-annotated acceleration data', Int. Conf. on Pervasive Computing, 2004, p. 1–17.
    5. 5)
      • Liu, R., Zhou, J., Liu, M., Hou, X.: `A wearable acceleration sensor system for gait recognition', IEEE Conf. on Industrial Electronics and Applications, 2007, p. 2654–2659.
http://iet.metastore.ingenta.com/content/journals/10.1049/el.2009.2301
Loading

Related content

content/journals/10.1049/el.2009.2301
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address