Name
Abstract | ||
|---|---|---|
We investigate how the acoustic properties of the pinna – i.e. the outer flap of the ear- and the ear canal can be used as
a biometric. The acoustic properties can be measured relatively easy with an inexpensive sensor and feature vectors can be
derived with little effort. Classification results for three platforms are given (headphone, earphone, mobile phone) using
noise as an input signal. Furthermore, preliminary results are given for the mobile phone platform where we use music as an
input signal. We achieve equal error rates in the order of 1%-5%, depending on the platform that is used to do the measurement.
|
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11608288_93 | International Conference on Biometrics |
Keywords | Field | DocType |
acoustic property,equal error rate,acoustic ear recognition,input signal,mobile phone,outer flap,ear canal,feature vector,classification result,inexpensive sensor,mobile phone platform | Ear recognition,Computer vision,Feature vector,Pinna,Computer science,Musical acoustics,Speech recognition,Artificial intelligence,Biometrics,Mobile phone,Linear discriminant analysis,Ear canal | Conference |
Volume | ISSN | ISBN |
3832 | 0302-9743 | 3-540-31111-4 |
Citations | PageRank | References |
2 | 0.43 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anton H. M. Akkermans | 1 | 170 | 10.79 |
| Tom A. M. Kevenaar | 2 | 344 | 21.90 |
| Daniel W. E. Schobben | 3 | 2 | 0.43 |