Abstract: 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 representation and classification method should be accurate and less time consuming.Aiming to satisfy these criteria we coupled the HOG descriptor (Histograms of Oriented Gradients) with the Random Forest classifier (RF). Although rarely used in face recognition, HOG have proven to be a power descriptor in this task with a lower computational time. As regards classification method, recent works have shown that apart from their accuracy when compared with its competitors, Random Forest exhibits a low computational time in both training and testing phase. Experimental ...
In this paper we propose a human detection framework based on an enhanced version of Histogram of Or...
Traditional facial recognition methods depend on a large number of training samples due to the massi...
In this paper, we propose a method to apply the popular cascade classifier into face recognition to ...
Efficient face descriptors require a careful equilibration between accuracy and feature dimension. I...
Since the Viola-Jones seminal work, the boosted cascade with simple features has become the most pop...
A facial classification system that utilises images of faceparts is presented in this paper. Each fa...
In this paper, a novel real-time human detection system based on Viola’s face detection framework an...
Facial recognition has been a long-standing problem in computer vision. Recently, Histograms of Orie...
We present a system for detecting and recognizing faces in images in real-time which is able to lear...
Face recognition is one of the challenging biometric technologies which has widespread applications ...
Human face recognition is the hottest topic in this era due to its importance in identity authentica...
The Single Sample per Person Problem is a challenging problem for face recognition algorithms. Patch...
International audienceRecently, Histograms of Oriented Gradient (HOG) are applied in face recognitio...
In this paper we propose a human detection framework based on an enhanced version of Histogram of Or...
Due to its wide range of use in human face-related applications, face detection has been considered ...
In this paper we propose a human detection framework based on an enhanced version of Histogram of Or...
Traditional facial recognition methods depend on a large number of training samples due to the massi...
In this paper, we propose a method to apply the popular cascade classifier into face recognition to ...
Efficient face descriptors require a careful equilibration between accuracy and feature dimension. I...
Since the Viola-Jones seminal work, the boosted cascade with simple features has become the most pop...
A facial classification system that utilises images of faceparts is presented in this paper. Each fa...
In this paper, a novel real-time human detection system based on Viola’s face detection framework an...
Facial recognition has been a long-standing problem in computer vision. Recently, Histograms of Orie...
We present a system for detecting and recognizing faces in images in real-time which is able to lear...
Face recognition is one of the challenging biometric technologies which has widespread applications ...
Human face recognition is the hottest topic in this era due to its importance in identity authentica...
The Single Sample per Person Problem is a challenging problem for face recognition algorithms. Patch...
International audienceRecently, Histograms of Oriented Gradient (HOG) are applied in face recognitio...
In this paper we propose a human detection framework based on an enhanced version of Histogram of Or...
Due to its wide range of use in human face-related applications, face detection has been considered ...
In this paper we propose a human detection framework based on an enhanced version of Histogram of Or...
Traditional facial recognition methods depend on a large number of training samples due to the massi...
In this paper, we propose a method to apply the popular cascade classifier into face recognition to ...