id: 05961001
dt: a
an: 05961001
au: Yang, Yong; Tian, Kan; Chen, Zhengrong
ti: A robust face recognition method based on adaboost, EHMM and sample
    perturbation.
so: Yao, JingTao (ed.) et al., Rough sets and knowledge technology. 6th
    international conference, RSKT 2011, Banff, Canada, October 9‒12,
    2011. Proceedings. Berlin: Springer (ISBN 978-3-642-24424-7/pbk).
    Lecture Notes in Computer Science 6954. Lecture Notes in Artificial
    Intelligence, 428-433 (2011).
py: 2011
pu: Berlin: Springer
la: EN
cc: 
ut: Face recognition; AdaBoost; EHMM; Sample perturbation
ci: 
li: doi:10.1007/978-3-642-24425-4_56
ab: Summary: Face recognition is a classical topic in pattern classification,
    although there are already some good methods and applications, robust
    face recognition methods are always pursued. In this paper, based on
    AdaBoost, embedded hidden Markov model (EHMM), and sample perturbation,
    a novel and robust face recognition method is proposed. Experiments
    results show that the proposed method can get higher recognition rate
    on benchmark datasets. Furthermore, the proposed method show robustness
    on the test samples with different illumination and shelter.
rv: