Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model
نویسندگان
چکیده
منابع مشابه
Single-Sample Face Recognition Based on Intra-Class Differences in a Variation Model
In this paper, a novel random facial variation modeling system for sparse representation face recognition is presented. Although recently Sparse Representation-Based Classification (SRC) has represented a breakthrough in the field of face recognition due to its good performance and robustness, there is the critical problem that SRC needs sufficiently large training samples to achieve good perfo...
متن کاملA Local Min-Max Binary Pattern Based Face Recognition Using Single Sample per Class
In this paper, we propose a new representation, called Local Min-Max Binary Pattern (LMin-MaxBP), and apply it to face recognition with single sample per class. The local appearance based methods have been successfully applied to face recognition and achieved state-of-the-art performance. The Local Binary Pattern (LBP) has been proved to be effective for image representation. The motivation for...
متن کاملSingle-sample face recognition based on improved SRC and expanding sample
Zhijing Xu ,Li Ye, Xiangjian He a Shanghai Maritime University, Shanghai ,China b University of Technology Sydney,Australia Abstract This paper proposes a kind of face recognition method with one training image per person, which is based on compressed sensing. There are two methods—nonlinear dimensionality reduction by locally linear embedding and sparse coefficients, by which redundant samples...
متن کاملFace Recognition in Thermal Images based on Sparse Classifier
Despite recent advances in face recognition systems, they suffer from serious problems because of the extensive types of changes in human face (changes like light, glasses, head tilt, different emotional modes). Each one of these factors can significantly reduce the face recognition accuracy. Several methods have been proposed by researchers to overcome these problems. Nonetheless, in recent ye...
متن کاملA New Face Recognition Algorithm based on Dictionary Learning for a Single Training Sample per Person
The number of the training samples per person has a significant impact on face recognition (FR) performance. For the single training sample per person (STSPP) problem, most traditional FR algorithms exhibit performance degradation owing to the limited information available to predict the variance of the query sample. This paper proposes a new method for the STSPP problem in FR, namely the Learn...
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: Sensors
سال: 2015
ISSN: 1424-8220
DOI: 10.3390/s150101071