TY - GEN
T1 - Fusion of visual and infrared face biometric scores by projection
AU - Toh, Kar Ann
PY - 2009
Y1 - 2009
N2 - This paper presents a projection model to fuse the scores of a visual face verification system and an infrared face verification system. Essentially, the model consists of an arbitrarily number of linear projection vectors with randomly permuted elements. An equal error rate formulation is next adopted to learn the linear coefficients for projection. The learned model is consequently used for prediction of verification states of unseen data. Our empirical evaluation using a moderate size data set shows potential of the proposed method.
AB - This paper presents a projection model to fuse the scores of a visual face verification system and an infrared face verification system. Essentially, the model consists of an arbitrarily number of linear projection vectors with randomly permuted elements. An equal error rate formulation is next adopted to learn the linear coefficients for projection. The learned model is consequently used for prediction of verification states of unseen data. Our empirical evaluation using a moderate size data set shows potential of the proposed method.
UR - http://www.scopus.com/inward/record.url?scp=77951140486&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951140486&partnerID=8YFLogxK
U2 - 10.1109/TENCON.2009.5396097
DO - 10.1109/TENCON.2009.5396097
M3 - Conference contribution
AN - SCOPUS:77951140486
SN - 9781424445479
T3 - IEEE Region 10 Annual International Conference, Proceedings/TENCON
BT - TENCON 2009 - 2009 IEEE Region 10 Conference
T2 - 2009 IEEE Region 10 Conference, TENCON 2009
Y2 - 23 November 2009 through 26 November 2009
ER -