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<>单目测距(目标检测+标定+测距)
实时感知本车周围物体的距离对高级驾驶辅助系统具有重要意义,当判定物体与本车距离小于安全距离时便采取主动刹车等安全辅助功能,这将进一步提升汽车的安全性能并减少碰撞的发生。上一章本文完成了目标检测任务,接下来需要对检测出来的物体进行距离测量。首先描述并分析了相机成像模型,推导了图像的像素坐标系与世界坐标系之间的关系。其次,利用软件标定来获取相机内外参数并改进了测距目标点的选取。最后利用测距模型完成距离的测量并对采集到的图像进行仿真分析和方法验证。
<>5.1 单目视觉测距与双目视觉测距对比
测距在智能驾驶的应用中发挥着重要作用。测距方法主要包含两类:主动测距与被动测距,主动测距是当前研究的热点内容之一。主动测距方法包括采用传感器、摄像机、激光雷达等车载设备进行测距。摄像头由于价格相对低廉且性能稳定应用较为广泛,本文采用摄像头进行距离测量。
单目测距主要运用测距模型结合目标矩形框来进行测距任务,通过目标在图像中的大小位置信息去估算距离。单目测距算法具有计算量小、成本低廉的优点,并且测距误差也可以通过后续的调校来消除,很多算法都在采用基于单目视觉传感器来开发产品。因此相对其他测距方法,单目视觉有更成熟的算法,本文亦采用单目视觉测距。
利用双目视觉可以获取同一物体在成像平面上的像素偏移量。然后可以使用相机焦距、像素偏移以及两个相机之间的实际距离从数学上得出对象之间的距离。与单目测距相比,双目测距虽然更加精确,不需要数据集,但计算量大,速度相对较慢,而且由于使用了两个摄像头,成本也变得更高