2.5D gait biometrics using the Depth Gradient Histogram Energy Image

Martin Hofmann, Sebastian Bachmann, Gerhard Rigoll

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

79 Zitate (Scopus)

Abstract

Using gait recognition methods, people can be identified by the way they walk. The most successful and efficient of these methods are based on the Gait Energy Image (GEI). In this paper, we extend the traditional Gait Energy Image by including depth information. First, GEI is extended by calculating the required silhouettes using depth data. We then formulate a completely new feature, which we call the Depth Gradient Histogram Energy Image (DGHEI). We compare the improved depth-GEI and the new DGHEI to the traditional GEI. We do this using a new gait database which was recorded with the Kinect sensor. On this database we show significant performance gain of DGHEI.

OriginalspracheEnglisch
Titel2012 IEEE 5th International Conference on Biometrics
UntertitelTheory, Applications and Systems, BTAS 2012
Seiten399-403
Seitenumfang5
DOIs
PublikationsstatusVeröffentlicht - 2012
Veranstaltung2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012 - Arlington, VA, USA/Vereinigte Staaten
Dauer: 23 Sept. 201227 Sept. 2012

Publikationsreihe

Name2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012

Konferenz

Konferenz2012 IEEE 5th International Conference on Biometrics: Theory, Applications and Systems, BTAS 2012
Land/GebietUSA/Vereinigte Staaten
OrtArlington, VA
Zeitraum23/09/1227/09/12

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