Study On Pedestrian Recognition Ahead Of Vehicle And Collision Warning System

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 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 difficult part of target detection. Although the study for object detection and tracking has been more than ten years in computer vision community, it is still an active research area. At present, there is not a target detecting and tracking system which is general, accurate, robust, efficient and real-time. Due to the human body is non-rigid, the scenes are complex, and there are plenty of interactions among the pedestrians or between the pedestrians and the scenes, the human detecting and tracking is one of the most challenges in computer vision.In this paper, a monocular vision sensor is used to get the environmental information in front of the vehicles for people detection technology research. Use the statistical learning methods for the recognition of pedestrian, study the various features of the pedestrian and extract the edge characteristics, texture features, gradient features and haar features of pedestrians as the input of the classifier training. Then use the AdaBoost algorithm and SVM algorithm to train the classifier to get a better pedestrian classification.Test result shows that the proposed method can identify effectively of the pedestrians in front of the vehicles, for pedestrians static and movement both have good results, and the real-time of the system is good.After the pedestrians are detected, this paper takes advantage of the Kalman filter method to predict the changes of the pedestrian rectangle parameters so that the pedestrians dan be tracked. At last, an early warning model of people and vehicles safety distance is established. According to the detection results from the visual sensors, improve the safety distance warning model then determine the values of some parameters, and then comprehensive the conditions of the people, the car and the road to calculate the people and vehicles safety early warning distance. Monocular vision technology is used to estimate the distance and the moving direction of pedestrians so that provide a basis to the car on when to warning, when to decelerate and when to brake. Then a pedestrian detection and warning system is designed...