TY - GEN
T1 - Open-set face recognition by transductive kernel associative memory
AU - Zhang, Bailing
AU - Hao, Hong
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/6
Y1 - 2014/1/6
N2 - Though a variety of face recognition techniques have been proposed in the literature, only a few of them considered open set recognition problems, which involves the rejection of unregistered subjects in addition to identifying persons registered in the database. Transductive confidence machine (TCM) is a novel strategy for classification associated with valid confidence, with recognition reliability as the ground for rejection. Many popular classification algorithms, such as k-nearest neighbor (kNN), can be plugged into the TCM framework and applied to open-set face recognition. As kernel associative memory model (KAM) has been proposed earlier as an efficient tool for close-set face recognition, this paper extends the KAM model into TCM by proposing a novel nonconformity measurement and corresponding TCM-kAM algorithm. Performance comparisons with published TCM-KNN open-set face recognition methods were conducted with ORL and AR faces, with verified advantages.
AB - Though a variety of face recognition techniques have been proposed in the literature, only a few of them considered open set recognition problems, which involves the rejection of unregistered subjects in addition to identifying persons registered in the database. Transductive confidence machine (TCM) is a novel strategy for classification associated with valid confidence, with recognition reliability as the ground for rejection. Many popular classification algorithms, such as k-nearest neighbor (kNN), can be plugged into the TCM framework and applied to open-set face recognition. As kernel associative memory model (KAM) has been proposed earlier as an efficient tool for close-set face recognition, this paper extends the KAM model into TCM by proposing a novel nonconformity measurement and corresponding TCM-kAM algorithm. Performance comparisons with published TCM-KNN open-set face recognition methods were conducted with ORL and AR faces, with verified advantages.
KW - Open-set face recognition Tranductive confidence machine kernel associative memory model
UR - http://www.scopus.com/inward/record.url?scp=84946531487&partnerID=8YFLogxK
U2 - 10.1109/CISP.2014.7003856
DO - 10.1109/CISP.2014.7003856
M3 - Conference Proceeding
AN - SCOPUS:84946531487
T3 - Proceedings - 2014 7th International Congress on Image and Signal Processing, CISP 2014
SP - 633
EP - 638
BT - Proceedings - 2014 7th International Congress on Image and Signal Processing, CISP 2014
A2 - Wan, Yi
A2 - Sun, Jinguang
A2 - Nan, Jingchang
A2 - Zhang, Quangui
A2 - Shao, Liangshan
A2 - Wang, Lipo
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2014 7th International Congress on Image and Signal Processing, CISP 2014
Y2 - 14 October 2014 through 16 October 2014
ER -