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 …

Face recognition algorithms can be divided into two categories: holistic and local feature-
based approaches. Holistic methods are very popular in recent years due to their good …

We propose a novel face image representation–Local gab or dominant direction pattern
(LGDDP) for face recognition. The face image is convolved with the Gabor filters, resulting in …

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 …

Linear regression classification (LRC) has attracted a great amount of attention owning to its
promising performance in face recognition. However, its performance will dramatically …

Selection and implementation of a face descriptor that is both discriminative and
computationally efficient is crucial. Local Binary Patterns (LBP) and Histogram of Oriented …

The efficient face recognition systems are those which are able to achieve higher
recognition rate with lower computational cost. To develop such systems both feature …

The combining classifier approach has proved to be a proper way for improving recognition
performance in the last two decades. This paper proposes to combine local and global facial …

Extracting holistic features from the whole face and extracting the local features from the sub-
image have pros and cons depending on the conditions. In order to effectively utilize the …