结合立体视觉与超像素技术的道路障碍物概率检测
Probability Detection of Road Obstacles Combining with Stereo Vision and Superpixels Technology

针对道路障碍物检测问题，提出了一种基于立体视觉与超像素技术的双目障碍物概率检测算法。该算法首先利用双目相机采集的左右视图进行立体匹配获取视差图，通过三维重建到得3D点云，然后采用最小二乘法拟合地平面方程，并计算图像空间点到地平面的距离，接着使用SLIC算法得到超像素，并计算超像素到地平面的中值距离，最后使用逻辑回归方法和信任函数计算像素为障碍物的概率。实验结果表明，该方法能够可靠地检测道路障碍物，并为障碍物检测的多传感器融合方法提供有价值的概率数据。
Aiming at the road obstacle detection, the obstacle probability detection algorithm based on the stereo vision and superpixel technology is proposed. Firstly, the disparity map was obtained by using stereo matching on the left and right images captured by using binocular cameras, and the 3D point cloud was reconstructed. Then the least square method was used to estimate the ground plane equation and calculate the distance from the image space point to the ground plane. After that, the superpixels were obtained by using SLIC algorithm, and the median distance of the superpixels to the ground plane were calculated. Finally, the probability of the pixel being an obstacle was calculated by using the logistic regression method and the belief function. The experimental results show that the present method can detect road obstacles reliably and provide the valuable probabilistic data for multi-sensor fusion methods of obstacle detection