منابع مشابه
Ear Recognition from One Sample Per Person
Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per ...
متن کاملFace Recognition from One Sample per Person
As one of the most visible applications in computer vision communication, face recognition (FR) has become significant role in the community. In the past decade, researchers have been devoting themselves to addressing the various problems emerging in practical FR applications in uncontrolled or less controlled environment. In many practical applications of FR (e.g., law enforcement, e-passport,...
متن کاملLow-resolution face recognition with single sample per person
As a growing number of low-resolution (LR) face images are captured by surveillance cameras, LR face recognition has been a hot issue for recent years. Previous efforts on LR face recognition typically assume each subject has multiple high-resolution (HR) training samples. However, this assumption may not hold in some special cases such as law-enforcement where only a single HR sample per perso...
متن کاملFace recognition with one sample per person based on contourlet and nearest feature line
In this paper, a novel algorithm for face recognition with one sample per person is proposed. The proposed algorithm is based on contourlet. Multiple training images for each class are constructed through the decomposition and reconstruction of original training images by contourlet. Thus neighborhood discriminant nearest feature line analysis can be performed on the new database. The experimen...
متن کاملMaking FLDA applicable to face recognition with one sample per person
In face recognition, the Fisherface approach based on Fisher linear discriminant analysis (FLDA) has obtained some success. However, FLDA fails when each person just has one training face sample available because of nonexistence of the intra-class scatter. In this paper, we propose to partition each face image into a set of sub-images with the same dimensionality, therefore obtaining multiple t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: PLOS ONE
سال: 2015
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0129505