基于激光雷达和摄像机的前方车辆检测
Preceding Vehicle Detection Based on Laser and CCD
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摘要: 考虑到激光雷达和机器视觉间信息的互补性,提出了一种融合图像和雷达信息的前方目标车辆检测方法.分析激光雷达数据的特点,提出了改进的基于密度的空间聚类算法实现雷达数据的聚类.目标车辆检测时,首先通过信息融合确定车辆的初始检测区域,生成车辆假设;然后利用模糊推理系统融合车辆多个特征验证车辆假设,实现车辆检测.试验结果表明,算法实现了无约束条件下的目标车辆检测,并且具有较好的适应能力和抗干扰能力,能准确地检测前方目标车辆.Abstract: Considering the complementarities of data obtained by radar and computer vision, a method of preceding vehicle detection using the image and the radar data was proposed. The improved DBSCAN was proposed to process the laser data according to their characteristics. During the vehicle detection, the vehicle hypothesis was generated with the fusion of laser data and image. After vehicle hypothesis formation, then, features were fuzzed and the vehicle detection was realized according to the confidence obtained by fuzzy inference system. The results indicate that the algorithm can detect vehicle without constricts of lane lines and it has good adaptive ability and anti-jamming ability. It can detect the proceeding vehicles accurately.