In this paper, we present an approach for crowd detection based on an ensemble of classifiers which employ several feature representation schemes of crowd images, including, local ternary patterns, local binary patterns, and features based on the spatial gray level dependency matrix. A Support Vector Machine classifier is trained on each of these feature vectors. Classifier predictions are then...

Face recognition is one of the important and popular visual recognition problem due to its challenging nature and its diverse set of applications. That‘s why face recognition is attracted by many researchers. Methods based on Local Binary Pattern (LBP) are widely used for face recognition in the literature, and it is sensitive to noise. To address this present paper utilized the powerful local ...

Detecting pedestrians in images plays a very important role 6 in many computer vision applications such as video surveillance, smart 7 cars and robotics. Feature extraction is the key for this task. Promis8 ing features should be discriminative, robust and easy to compute. This 9 paper presents a novel and efficient feature, termed pyramid center10 symmetric local binary\ternary patterns (pyram...

Detecting pedestrians in images and videos plays a critically important role in many computer vision applications. Extraction of effective features is the key to this task. Promising features should be discriminative, robust to various variations and easy to compute. In this work, we presents a novel feature, termed pyramid center-symmetric local binary/ternary patterns (pyramid CS-LBP/LTP), fo...

Recent work on background subtraction has shown developments on two major fronts. In one, there has been increasing sophistication of probabilistic models, from mixtures of Gaussians at each pixel [8], to kernel density estimates at each pixel [1], and more recently to joint domainrange density estimates that incorporate spatial information [7]. Another line of work has shown the benefits of in...

Local Binary Patterns and various derivatives of the method have been widely used in the field of texture recognition over the past 15 years. A restriction of these methods is their variance with respect to affine transformations of an image. This is caused by the fixed circular neighborhood and the fixed support area of sampling points. The main approach to deal with affine transformations suc...