Study On Pedestrian Recognition Ahead Of Vehicle Based On Monocular Vision

Computer vision based pedestrian detection has become one of the hottest topics in the domain of computer vision and intelligent vehicle because of its potential applications in driver assistance systems. It aims at detecting pedestrians appearing ahead of the vehicle using a vehicle-mounted camera, so as to assess the danger and take actions to protect pedestrians in case of danger.Pedestrian detection are part of the target detection, at the same time, pedestrian detection is a major area of difficulty of target detection. Although the object detection and tracking has been studied for more than ten years in computer vision community, it is still an active research area. In present, there is not an object detection and tracking system which is general, robust, accurate, efficient, and real time. Because the human body is non-rigid, the scenes are cluttered, and there are a lot of interactions among the pedestrians or between the pedestrians and the scenes, the human detection and tracking is one of the most difficult challenges among those tasks mentioned above.In this paper, a single-vision sensors as the means of the vehicle to access to environmental information in front of the vehicles, For people detection technology research. A typical pedestrian detection system includes two modules:regions of interest(ROIs) segmentation and object recognition. This paper introduces the principle of typical methods of the two modules and analyzes their respective pros and cons, and proposed new pedestrian segmentation method from traditional way.This paper applies the AdaBoost algorithm which originates from face detection to pedestrian detection, found a pedestrian segmentation method that AdaBoost algorithm and pedestrian shape features integration, separate pedestrian candidate target form the area in front of vehicles of different regions, in order to detect pedestrians more quickly. According to the gray images of pedestrians have a certain symmetry texture features and characteristics of gray, while the continuous verge of pedestrians make the outline of image features Obviously, using SVM algorithm to train the classification of pedestrians recognition.Test results show that the proposed method can identify effectively of different sizes, colors and shapes of the pedestrian who in front of the vehicles, for static and pedestrian movement have good test results, the real-time system is better.