向文辉, 刘羽, 曹洋, 汪增福. 基于车载单目图像的3维地平面估计[J]. 机器人, 2014, 36(1): 76-82. DOI: 10.3724/SP.J.1218.2014.00076
引用本文: 向文辉, 刘羽, 曹洋, 汪增福. 基于车载单目图像的3维地平面估计[J]. 机器人, 2014, 36(1): 76-82. DOI: 10.3724/SP.J.1218.2014.00076
XIANG Wenhui, LIU Yu, CAO Yang, WANG Zengfu. 3D Ground Plane Estimation from a Monocular Vehicle-borne Image[J]. ROBOT, 2014, 36(1): 76-82. DOI: 10.3724/SP.J.1218.2014.00076
Citation: XIANG Wenhui, LIU Yu, CAO Yang, WANG Zengfu. 3D Ground Plane Estimation from a Monocular Vehicle-borne Image[J]. ROBOT, 2014, 36(1): 76-82. DOI: 10.3724/SP.J.1218.2014.00076

基于车载单目图像的3维地平面估计

3D Ground Plane Estimation from a Monocular Vehicle-borne Image

  • 摘要: 提出了一种由车载摄像头获取的单目图像估计场景的3维地平面以及深度信息的算法.该算法首先融合图像的散焦信息、饱和度信息以及暗通道先 验,得到场景的相对深度图.然后在基于地平线分段平滑的假设下,进行双边中值滤波推断出3维地平面.最后在此基础上利用成像几何原理计算 出绝对深度图.为了验证算法的有效性,不仅在离线计算机上进行了大量的对比实验,而且还将该算法应用于机器人小车的室外自主避障.实验 结果表明本文算法可以较好地估计出3维地平面和场景深度,机器人小车可以利用这些信息成功检测并躲避障碍物.

     

    Abstract: An algorithm is proposed to estimate the 3D ground plane region and scene depth information from a monocular image captured by a vehicle-borne camera. Firstly, information about image defocus, image saturation and dark channel prior are fused to estimate a relative depth map of the scene. Then, the 3D ground plane can be inferred by using a bilateral median filter based on the assumption that the horizon is piecewise smooth. Finally, absolute depth map can be obtained by using the principle of imaging geometry. To verify the effectiveness of the proposed algorithm, not only numerous comparative experiments are performed on an offline computer, but also it is applied to the outdoor autonomous obstacle avoidance of a robot vehicle. Experiment results demonstrate that both the 3D ground plane and scene depth information can be well estimated by the proposed algorithm, with which the robot vehicle can successfully detect and avoid the obstacles.

     

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