Robust obstacle detection with monocular vision based on motion analysis

Cédric Demonceaux, D. Kachi-Akkouche
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引用次数: 21

Abstract

This paper deals with the problem of obstacle detection from a single camera mounted on a vehicle. We define an obstacle as any object that obstructs the vehicle's driving path. The perception of the environment is performed through a fast processing of image sequence. The approach is based on motion analysis. Generally, the optical flow techniques are huge in computation time and sensitive to vehicle motion. To overcome these problems, we choose to detect the obstacle in two steps. The road motion is firstly computed through a fast and robust wavelets analysis. Then, we detect the areas which have a different motion thanks to a Bayesian modelization. Results shown in the paper prove that the proposed method permits the detection of any obstacle on a road.
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基于运动分析的单目视觉鲁棒障碍检测
本文研究了车载单摄像头的障碍物检测问题。我们将障碍物定义为阻碍车辆行驶路径的任何物体。通过对图像序列的快速处理来实现对环境的感知。该方法基于运动分析。一般来说,光流技术计算时间大,对车辆运动敏感。为了克服这些问题,我们选择分两步检测障碍物。首先通过快速鲁棒小波分析计算道路运动;然后,我们通过贝叶斯建模来检测具有不同运动的区域。实验结果表明,该方法可以检测到道路上的任何障碍物。
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