自主驾驶与辅助导航是目前国际上研究的热点问题.通过对室外行驶车辆上的CCD摄像机所采集的长序列立体图象的处理与分析,研究公路汽车自动视觉导航中的道路识别与跟踪问题.该文提出一种基于长序列立体图\r\n象处理的三维运动参数估计算法,算法的核心是采用了能有效抑制噪声的边缘检测模板,建立了车辆行驶过程中的道路曲率动态模型、车自身的运动模型和摄像机的透视投影模型,并通过卡尔曼滤波器进行三维运动参数的估计.算法具有快速、鲁棒性好及实用性强的优点.文章还给出了在室外环境下拍摄的真实图象的实验结果.实验证明

The problem of autonomous driving and co-navigating has received increasing attention in recent years. This paper researches on road recognition and tracking in automatic visual road vehicle guidance system by processing and analysing a long sequence stereo images of real road which are gathered on an autonomous vehicle driveing outside. An algorithm is proposed for estimating the parameters of three-dimensional motion, based on long sequence stereo images processing. It is our core method to build the road's curvature dynamic model, vehicle's state kinematic model and camera's perspective model, and to estimate the 3D motion parameters using Kalman filter. The algorithm is fast,robust and practical. Experimental results with real scene images are given. Experiments prove that the results are satisfying for road recognition and tracking, so the approach could actively improve the research on the performance of the visual road vehicle guidance system.