1、外文标题： Fast pedestrian detection and dynamic tracking for intelligent vehicles within V2V cooperative environment 外文作者： Fuliang Li, Ronghui Zhang , Feng You 文献出处： Iet Image Processing , 2017 , 11 (10) :833-840 英文 2203单词， 14998字符，中文 3668汉字。 此文档是外文翻译成品，无需调整复杂的格式哦！下载之后直接可用，方便快捷！只
2、需二十多元。 原文： Fast pedestrian detection and dynamic tracking for intelligent vehicles within V2V cooperative environment Fuliang Li, Ronghui Zhang , Feng You Abstract: Pedestrian detection has become one of the hottest topics in intelligent traffic system because of its potentia
3、l applications in driver assistance and automatic driving. In this study, a fast pedestrian detection and dynamic tracking method within vehicle-to-vehicle (V2V) cooperative environment is proposed. A dynamic tracking-by-detection framework for real-time pedestrian detection is developed. First, a c
4、ascade classifiers, based on selected Haar-like features, is trained to detect pedestrian. Then, CamShift algorithm combined with extended Kalman filtering is used to pedestrian dynamic tracking. Finally, with the crowdsourcing detected information, a smartphone-based V2V cooperative warning system
5、is developed to share useful detection results within blind spots. The experiment results show that the proposed method has a real-time and accurate performance, which can provide a reference for road traffic safety monitoring technology. Introduction In recent years, pedestrian deaths resulting fro
6、m the complex traffic environment accounted for 60% of all deaths on the roads 1. Aiming to reduce collision and danger to pedestrians from traffic, pedestrian active safety analysis has become an international research focus, especially pedestrian detection technology. In general, pedestrian detection methods can be divided into target characteristics template-based and pedestrian-based learning methods. The former type of methods cost less and are relatively simple. However, those methods only work well by detected obvious conto
