TY - GEN
T1 - Towards fast 3D ear recognition for real-life biometric applications
AU - Passalis, G.
AU - Kakadiaris, I. A.
AU - Theoharis, T.
AU - Toderici, G.
AU - Papaioannou, T.
PY - 2007
Y1 - 2007
N2 - Three-dimensional data are increasingly being used for biometric purposes as they offer resilience to problems common in two-dimensional data. They have been successfully applied to face recognition and more recently to ear recognition. However, real-life biometric applications require algorithms that are both robust and efficient so that they scale well with the size of the databases. A novel ear recognition method is presented that uses a generic annotated ear model to register and fit each ear dataset. Then a compact biometric signature is extracted that retains 3D information. The proposed method is evaluated using the largest publicly available 3D ear database appended with our own database, resulting in a database containing data from multiple 3D sensor types. Using this database it is shown that the proposed method is not only robust, accurate and sensor invariant but also extremely efficient, thus making it suitable for real-life biometric applications.
AB - Three-dimensional data are increasingly being used for biometric purposes as they offer resilience to problems common in two-dimensional data. They have been successfully applied to face recognition and more recently to ear recognition. However, real-life biometric applications require algorithms that are both robust and efficient so that they scale well with the size of the databases. A novel ear recognition method is presented that uses a generic annotated ear model to register and fit each ear dataset. Then a compact biometric signature is extracted that retains 3D information. The proposed method is evaluated using the largest publicly available 3D ear database appended with our own database, resulting in a database containing data from multiple 3D sensor types. Using this database it is shown that the proposed method is not only robust, accurate and sensor invariant but also extremely efficient, thus making it suitable for real-life biometric applications.
UR - http://www.scopus.com/inward/record.url?scp=44849113202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=44849113202&partnerID=8YFLogxK
U2 - 10.1109/AVSS.2007.4425283
DO - 10.1109/AVSS.2007.4425283
M3 - Conference contribution
AN - SCOPUS:44849113202
SN - 9781424416967
T3 - 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007 Proceedings
SP - 39
EP - 44
BT - 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007 Proceedings
T2 - 2007 IEEE Conference on Advanced Video and Signal Based Surveillance, AVSS 2007
Y2 - 5 September 2007 through 7 September 2007
ER -