一种基于多传感器融合的车辆检测与跟踪方法

针对城市道路环境，提出了一种基于激光雷达和视觉的车辆检测与跟踪方法.首先，采用透视变换和多传感器联合标定，根据激光雷达数据生成包含车辆假设的兴趣区域，以提高车辆检测的可靠性和降低图像处理的计算量；然后，提出了一种基于多维特征空间马氏距离的车辆检测算法，通过提取兴趣区域内图像特征向量，并将其与标准向量间的马氏距离作为车辆状态估计；最后，采用Kalman滤波实现车辆运动跟踪.为了提高鲁棒性，将粒子滤波算法与Kalman滤波相结合，以在雷达信息不准确的情况下准确地实现目标状态估计.实验结果表明，该方法在城市环境中取得了比较理想的车辆跟踪效果.

Multi-sensor Fusion Based Vehicle Detection and Tracking Method

To fulfill real-time vehicle detection and track in city environment,a method based on laser radar and vision was presented.By perspective transform,vehicle hypothesis is done through laser radar.For vehicle recognition aspect,a method based on multi-dimension space Mahalanobis distance is presented,which extracts feature vector in ROI,and using the Mahalanobis distance between it and standard vector as presence probability.In vehicle tracking,the system uses Kalman filter to fulfill target tracking,at the ...