Research on Pedestrian’s Detection Based on the Integration of AdaBoost Algorithm and Shape Features

Abstract

Abstract. In this paper, propose a pedestrian detection method that based on AdaBoost algorithm and pedestrian shape features integration. First according to the collected pedestrian true, false sample, selected the characteristics of the extended class Haar, adopt AdaBoost algorithm training get pedestrian classifier to split the initial candidate region of all pedestrians in the image. In this paper, propose an adaptive threshold weight update method, significantly reduced the number of the characteristics of strong classifier, optimize the classifier structure, reduce the complexity of the algorithm; meanwhile, the online update detector, improving the reliability of the detector. Pedestrian leg have strong vertical edge symmetry characteristic so that extracted the vertical edge detection in the initial candidate region, According to the symmetry determine the vertical axis of symmetry, combined with the morphological characteristics of pedestrians to determine the width and height characteristics of the pedestrian, to determine the pedestrian candidate region, Finally, put a further validation to the pedestrian candidate region. IntroductionWith China's rapid increase in car ownership, frequency of road traffic accidents, especially the traffic accidents caused by vehicle and pedestrian collision, is the main reason for pedestrian casualties. It makes the application of safety driver assistance systems in our country with greater urgency and relevance. Detection of the pedestrian in front of the vehicle is one the Indispensable functions of the safety driver assistance systems. It can effectively help the driver timely respond to the external environment in the urban to avoid pedestrian collisions. For a pedestrian detection system, it should have a good real-time, low false alarm rate, good environment adaptability. Currently, the commonly used pedestrian segmentation method is edge detection, is mainly to split the pedestrian in road. This paper presents a pedestrian candidate region segmentation method based on the integration of the shape characteristics of the pedestrian and AdaBoost algorithm, extract the possible position of the pedestrians in the image, so that provide input for the effective identification of pedestrian. [1,2]