Shahali, Fatemeh, Nazemi, Azadeh and Azimifar, Zohreh
(2018)
Single sample face identification.
In: 2017 Artificial Intelligence and Signal Processing Conference (AISP), 25-27 Oct 2017, Shiraz, Iran.
This paper describes three methods to improve
single sample dataset face identification. The recent
approaches to address this issue use intensity and do not
guarantee the high accuracy under uncontrolled conditions.
This research presents an approach based on Sparse
Discriminative Multi Manifold Embedding (SDMME),
which uses feature extraction rather than intensity and
normalization for pre-processing to reduce the effects of
an uncontrolled condition such as illumination. In average this
study improves identification accuracy by about 17% compared to
current methods
Item Type:
Conference or Workshop Item (Paper)
Event Type:
Conference
Refereed:
Yes
Uncontrolled Keywords:
Face Identification; Sparse Discriminative Multi
Manifold Embedding (SDMME); Single Sample dataset; Feature
extraction; Self Quotient Image ( SQI)