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Detection and tracking of boundary of unmarked roads

机译:未标记道路边界的检测和跟踪

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This paper presents a new method of detecting and tracking the boundaries of drivable regions in road without road-markings. As unmarked roads connect residential places to public roads, the capability of autonomously driving on such a roadway is important to truly realize self-driving cars in daily driving scenarios. To detect the left and right boundaries of drivable regions, our method first examines the image region at the front of ego-vehicle and then uses the appearance information of that region to identify the boundary of the drivable region from input images. Due to variation in the image acquisition condition, the image features necessary for boundary detection may not be present. When this happens, a boundary detection algorithm working frame-by-frame basis would fail to successfully detect the boundaries. To effectively handle these cases, our method tracks, using a Bayes filter, the detected boundaries over frames. Experiments using real-world videos show promising results.
机译:本文提出了一种无需道路标记即可检测和跟踪道路上可行驶区域边界的新方法。由于未标记的道路将居民区与公共道路连接起来,因此在这种道路上自动驾驶的能力对于在日常驾驶场景中真正实现自动驾驶汽车至关重要。为了检测可驾驶区域的左右边界,我们的方法首先检查了自我车辆前部的图像区域,然后使用该区域的外观信息从输入图像中识别出可驾驶区域的边界。由于图像获取条件的变化,可能不会出现边界检测所需的图像特征。发生这种情况时,逐帧工作的边界检测算法将无法成功检测边界。为了有效处理这些情况,我们的方法使用贝叶斯过滤器跟踪帧上检测到的边界。使用现实世界的视频进行的实验显示出令人鼓舞的结果。

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