检索规则说明:AND代表“并且”;OR代表“或者”;NOT代表“不包含”;(注意必须大写,运算符两边需空一格)
检 索 范 例 :范例一: (K=图书馆学 OR K=情报学) AND A=范并思 范例二:J=计算机应用与软件 AND (U=C++ OR U=Basic) NOT M=Visual
作 者:靳璐[1,2] 付梦印[1,2] 王美玲[1,2] 杨毅[1,2]
机构地区:[1]北京理工大学自动化学院,北京100081 [2]复杂系统智能控制与决策教育部重点实验室,北京100081
出 处:《红外与毫米波学报》2014年第5期465-471,共7页Journal of Infrared and Millimeter Waves
基 金:Supported by the Nation Science Foundation of China(91120003);Nation Science Foundation of China(61105092);Beijing Natural Science Foundation(4101001)
摘 要:根据智能车辆主动驾驶辅助系统中的重要性,提出了一种融合毫米波雷达数据和视觉多特征的车辆检测算法。车辆检测算法通过三个步骤实现,首先,提出一种空间对准算法实现毫米波雷达和视觉的空间对准;其次,根据空间对准结果和搜索策略提取目标车辆的感兴趣区域;最后,融合车底阴影、对称轴、左右边缘等车辆特征实现车辆检测,其中,为了准确得到目标车辆的车底阴影,提出一种改进的车底阴影分割算法。算法的性能在不同的场景下得到证实,实验结果表明该车辆检测算法是有效和可靠的。With the importance of automotive drive assistance system of intelligent vehicle, vehicle detection fusing millimeter wave (MMW) radar data and vision multi-features is presented. The vehicle detection algorithm can be divided into three steps. Firstly, a space alignment algorithm between MMW radar and vision was proposed to get space alignment point according to the space transformation matrix of image coordinate and radar coordinate. The second step obtains region of interest (ROI) according to the space aligned point and search strategy. At last, vehi- cle detection was realized through features of vehicle including bottom shadow, symmetry, left and right edges ; in this step, an improved segmentation algorithm of bottom shadow of vehicle was described in order to obtain accu- rate vehicle width. The performance of the algorithm was verified under different scenarios. The results show the vehicle detection algorithm is effective and feasible.
关 键 词:主动驾驶辅助系统 车辆检测 空间对准 感兴趣区域 车底阴影
分 类 号:TP242[自动化与计算机技术—检测技术与自动化装置]
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在载入数据...
正在链接到云南高校图书馆文献保障联盟下载...
云南高校图书馆联盟文献共享服务平台 版权所有©
您的IP:216.73.216.15