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Advantages Of Pedestrian Detection

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A:10 Y. Chen
A Survey of Pedestrian Detection A:11
A Survey of Pedestrian Detection
YUECHEN, University of Ottawa
In recent years, with the rapidly increasing of automatic driving technology, pedestrian detection becomes a new and interesting area in computer vision. And the key applications are mostly in intelligent vehicles, surveillance, advanced robotics and so on. Since 2005, pedestrian detection has entered a stage of development, but there are still many problems to be solved, mainly in terms of the performance of detection and speed of it. In these years, many companies like Google, try their best to do the research about pedestrian detection, in order to ensure that during the autopilot will not threaten the safety of the pedestrians.This survey aims to provide an overview of the most useful methods of
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THE NETHODS BASED ON BACKGROUND MODELING
Introduction
Background modeling method is a method that we can use it to extract the objects in the foreground and the target area for the aim of feature extraction. After that we can use the classifier to classify and then we can judge whether this image include the pedestrian.
Though there are many advantages about background modeling,there still exists many disadvantages in background modeling method. At first, it must suit the change of environment. Many factors can result in the change of environment, such that illumination. If the illumination changes, the color of the images will change. For example, in the condition of sufficient light, the color of the grass will change from dark green to light green. This change will make the background modeling fails.
The second disadvantage of background modeling is that if the camera shakes, this will make the image shake. For example, if you hold your camera and take a picture, it is easy to get a blurred image, which is difficult to extract the features. Based on this reason, it is a kind of disadvantage of background
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