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中文摘要：
提出了一种融合激光雷达和单目摄像机的草丛中障碍物检测方法。首先由三维激光雷达测得一系列作为训练样本的距离数据，统计障碍物与杂草的形状特征参数，并利用期望最大（ExpectationMaximization）算法求得高斯混合模型（GaussianMixtureModel）来表征该特征值分布情况。利用该高斯混合模型可以从待测场景提取出候选障碍物区域。同时，采用均值偏移算法对场景的彩色图像进行分割，获得场景的区域信息。借助激光雷达和摄像机联合标定的结果，将激光雷达获得的候选障碍物区域投影至分割后的彩色图像，并进行融合获得最终障碍物判别结果。实验表明该方法能有效地检测出草丛中的障碍物，并具有较高的精度和较低的虚警率。
英文摘要：
A novel method for detecting obstacles in grass is proposed by fusing information from ladar and camera. Firstly, training range data is acquired by a 3-D ladar, and shape feature parameters of obstacles and grass are calculated respectively. Using Expectation Maximization （EM） algorithm, the Gaussian Mixture Model （GMM） which represents the distribution of shape features is learned. With these learned models, the 3-D points of candidate obstacles in the scene can be obtained. Meanwhile, mean-shift algorithm is applied to the corresponding color image to acquire the region information of the scene. With the result of joint calibration of the 3D ladar and the camera, those candidate obstacle points are projected to the segmented image and fusion is then performed to make the final decision. Experimental results show that the proposed method can distinguish obstacles from grass effectively with high precision and low false-alarm.
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