The histogram of oriented gradient has been successfully applied in many research fields
with excellent performance especially in pedestrian detection. However, the method has …

Histogram of oriented gradients (HOG) descriptor was initially applied to human detection
and achieved great success. In recent years, HOG descriptor has also been applied to face …

Face recognition has been a long standing problem in computer vision. Recently,
Histograms of Oriented Gradients (HOGs) have proven to be an effective descriptor for …

A novel object descriptor, histogram of Gabor phase pattern (HGPP), is proposed for robust
face recognition. In HGPP, the quadrant-bit codes are first extracted from faces based on the …

Face recognition is an important subject in computer vision and authentication systems.
Feature extraction is one of the main steps in the face recognition systems, which greatly …

The Gabor feature is effective for facial image representation, while linear discriminant
analysis (LDA) can extract the most discriminant information from the Gabor feature for face …

To effectively represent facial features in complex environments, a face recognition method
based on dense grid histograms of oriented gradients (HOG) is proposed. First, the face …

Robust descriptor-based subspace learning with complex data is an active topic in pattern
analysis and machine intelligence. A few researches concentrate the optimal design on …

Information jointly contained in image space, scale and orientation domains can provide rich
important clues not seen in either individual of these domains. The position, spatial …

A new method of face recognition based on gradient direction histogram (HOG) features
extraction and fast principal component analysis (PCA) algorithm is proposed to solve the …