基于透视点和轮廓的粘连车辆分割方法  

A Segmentation Method for the Occluded Vehicles Based on Perspective Points and Contours

作　　者：李宇成[1] 欧晓丹[1] 田震[1] 

机构地区：[1]北方工业大学自动化系,北京100144

出　　处：《计算机工程与科学》2011年第11期108-112,共5页Computer Engineering & Science

摘　　要：为解决视频车辆跟踪中经常出现的多辆车的前景粘连问题,本文提出了一种结合透视原理和车辆轮廓的粘连车辆分割方法。首先,通过分析路面场景中车道信息获取透视点,再利用透视点得到车辆的长方体透视模型,通过判断长方体模型的高宽比和长方体模型内部空缺区域的面积大小进行粘连检测,并根据粘连情况的不同选取相应的分割点搜索方法,从前往后顺序分割出粘连的车辆前景团块。实验表明,此方法对直线道路上多辆车粘连的分割有较好的准确度和适应性。The paper proposes a new method of combining perspective points and vehicle contours to segment the occluded vehicles in the image for resolving the problem of multi-vehicle occlusion in vehicle detecting and tracking. Perspective points are detected by analyzing the lane lines in the highway scene, and the cuboids of vehicle models are built with the perspective points. The ratio of the cuboid＇s height to width and the size of the vacant area inside the cuboid models are used to detect the occluded cars. Different searching methods are chosen to find the cut-points, depending on the condition of occlusion. Then, the occluded vehicles are detected and segmented in sequence from front to back. The experi- ments show the accuracy and adaptability of the proposed method in the segmentation of the occluded ve hicles on a straight road.

关 键 词：车辆粘连 分割 长方体模型 轮廓 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]