id: 05578587
dt: a
an: 05578587
au: Micheloni, Christian; Sangineto, Enver; Cinque, Luigi; Foresti, Gian Luca
ti: Improved statistical techniques for multi-part face detection and
    recognition.
so: Salberg, Arnt-Børre (ed.) et al., Image analysis. 16th Scandinavian
    conference, SCIA 2009, Oslo, Norway, June 15‒18, 2009. Proceedings.
    Berlin: Springer (ISBN 978-3-642-02229-6/pbk). Lecture Notes in
    Computer Science 5575, 331-340 (2009).
py: 2009
pu: Berlin: Springer
la: EN
cc: 
ut: 
ci: 
li: doi:10.1007/978-3-642-02230-2_34
ab: Summary: In this paper we propose an integrated system for face detection
    and face recognition based on improved versions of state-of-the-art
    statistical learning techniques such as Boosting and LDA. Both the
    detection and the recognition processes are performed on facial
    features (e.g., the eyes, the nose, the mouth, etc) in order to improve
    the recognition accuracy and to exploit their statistical independence
    in the training phase. Experimental results on real images show the
    superiority of our proposed techniques with respect to the existing
    ones in both the detection and the recognition phase.
rv: