One of the important goals of researchers in Artificial Intelligence and Robotics is to have a machine can like a human. On the way to achieve this goal, the machine should have a good perception of the environment. One of the essential information that a machine my have about its environment is to know who are where and what they are doing. Various solutions have been proposed to answer these questions that almost all of them are in the realm of Computer Vision which shows its importance in this application. In this research we have proposed a new method for pedestrian detection in images and videos. Our method uses sliding windows to search through images. Each window is divided into overlapping cells from which features are extracted. The feature that we extracted to describe each window is based on the analysis of the gradient distribution of each cell. After gradient distribution of a cell is computed, the PCA is applied on it and a mathematical expression is calculated as a feature of that cell. Then, features are left; MARGIN: 0cm 0cm 0pt; unicode-bidi: embed; DIRECTION: ltr" dir=ltr align=left Keywords: Computer Vision, Pedestrian Detection, Pattern Recognition, Aerial Images Segmentation
