计算机技术与发展2017，Vol.27Issue(10)：165-168,176,5.DOI:10.3969/j.issn.1673-629X.2017.10.035
基于Adaboost分类器的车辆检测与跟踪算法
A Vehicle Detection and Tracking Algorithm Based on Adaboost Classifier
摘要
Abstract
Vehicle detection and tracking is one of the most important research topics in the field of intelligent transportation. A real-time algorithm of vehicle detection and tracking based on Haar-like features and the Adaboost classifier is proposed to promote the construc-tion of safe city and assist vehicle driving. A large number of positive and negative sample images of vehicle are collected. The Haar-like features of the images are extracted based on the integral map and the Adaboost algorithm is exploited to do Haar-like features selection and classifier training for matching the pattern with the obtained classifier to realize the vehicles detection. The characteristics of the vehi-cles in the adjacent frames are matched to complete vehicles tracking. By calibrating scene,the vehicle speed measurement and traffic sta-tistics have been achieved based on vehicles tracking. Experimental results in real road scene show that it can effectively conduct vehicle detection and tracking in real-time for alleviating the traffic pressure to some extent and can implement vehicle speed measurement and traffic statistics accurately,which has provided the relevant basis for speeding and road congestion with an excellent application prospect.关键词
车辆检测与跟踪/类Haar特征/Adaboost算法/测速/车流量统计Key words
vehicle detection and tracking/Haar-like features/Adaboost algorithm/speed measurement/traffic statistics分类
信息技术与安全科学引用本文复制引用
陈拥权,陈影,陈学三..基于Adaboost分类器的车辆检测与跟踪算法[J].计算机技术与发展,2017,27(10):165-168,176,5.基金项目
安徽省自主创新专项资金计划项目(13Z02005) （13Z02005）
