交通视觉中鲁棒目标检测方法研究

项目名称： 交通视觉中鲁棒目标检测方法研究

项目编号： No.61273274

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 自动化技术、计算机技术

项目作者： 苗振江

作者单位： 北京交通大学

项目金额： 80万元

中文摘要： 随着我国高速公路与高速铁路的快速建设，对如何减少交通事故，确保运输安全提出了新的挑战。智能视频监控是保障交通安全的重要手段之一，它可有效检测交通线路中的车辆、行人、道路等情况和异常，具有巨大的应用前景，但其中的关键技术目标检测没有得到有效解决，不能有效处理复杂交通环境中的光照变化、雨雪扰动、摄像机摇动、目标遮挡及外观变化等情况下的目标检测。本申请项目针对交通场景目标检测所存在的问题，研究解决干扰背景中运动目标的鲁棒检测、背景运动（摄像机非静止）情况下的运动目标的鲁棒检测、复杂前景中特定目标的鲁棒检测三方面问题，提出了基于亮度补偿与局部核直方图的干扰背景下运动目标检测方法、基于分布式运动估计的运动背景下运动目标检测方法、基于图模型结构化描述的特定目标检测方法，并在此基础上设计实现一个针对复杂多变交通环境的鲁棒目标检测系统平台，验证理论方法，促进研究成果走向实用，应用于我国智能交通。

中文关键词： 目标检测；目标分类；目标分割；视频分析；智能交通

英文摘要： With the rapid development of highway and high-speed railway in our country, it becomes more and more important to reduce traffic accidents and ensure transportation safety. Intelligent video surveillance is an important means to provide traffic safety and has a great application prospect. It can effectively detect vehicles, pedestrians, road situation and anomaly in the traffic lines. But one of its key technologies-object detection-has not yet been solved effectively. Object detection still cannot be effectively used in some complex traffic environments like light changes, rain and snow disturbance, camera shake, target blocking and appearance changes. Aiming at the issues of object detection in traffic scene, this project studies: robust detection of moving targets in noise background; robust detection of moving objects in non-stationary background (camera with movement); robust detection of specific object in complex background. Three methods are proposed: moving object detection based on brightness compensation and local kernel histogram; moving object detection based on distributed motion estimation in moving background; specific object detection based on structural description with graph model. On this basis, a robust object detection system platform for complex and changing traffic environment will be

英文关键词： Object Detection；Object Classification；Object Segmentation；Video Analysis；Intelligent Transportation