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General information |
| Author |
Vesnicer, Boštjan; Gros, Jerneja Žganec; Pavešic, Nikola; Štruc, Vitomir |
| Published |
InTech Open Access Publisher, 2012
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| Abstract |
Face recognition in uncontrolled environments
remains an open problem that has not been satisfactorily
solved by existing recognition techniques. In this paper,
we tackle this problem using a variant of the recently
proposed Probabilistic Linear Discriminant Analysis
(PLDA). We show that simplified versions of the PLDA
model, which are regularly used in the field of speaker
recognition, rely on certain assumptions that not only result
in a simpler PLDA model, but also reduce the computational
load of the technique and ‐ as indicated by our
experimental assessments ‐ improve recognition performance.
Moreover, we show that, contrary to the general belief
that PLDA‐based methods produce well calibrated
verification scores, score normalization techniques can still
deliver significant performance gains, but only if nonparametric
score normalization techniques are employed.
Last but not least, we demonstrate the competitiveness of
the simplified PLDA model for face recognition by comparing
our results with the state‐of‐the‐art results from the
literature obtained on the second version of the large‐scale
Face Recognition Grand Challenge (FRGC) database. |
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International Journal of Advanced Robotic Systems
Author: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Published: 2004
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