基于NNF和HMM方法的车道边界检测与跟踪

2007 IEEE Intelligent Vehicles Symposium Pub Date : 2007-06-13 DOI:10.1109/IVS.2007.4290265

M. Boumediene, A. Ouamri, N. Dahnoun

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引用次数: 16

摘要

本文提出了一种新的车道检测与跟踪算法。在检测步骤中，从视频序列的第一帧开始，使用线性抛物模型来平滑使用NNF方法获得的估计轨迹。在跟踪步骤中，假设模型的变化很小，我们使用HMM来更新模型的每个参数。所得结果令人满意。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Lane Boundary Detection and Tracking using NNF and HMM Approaches

In this communication we present a new algorithm of lane detection and tracking. In the detection step, from the first frame of a video sequence, a linear-parabolic model is used to smooth the estimated trajectories, obtained by using the NNF approach. In the step of tracking, assuming a small change in the model, we use the HMM to update each parameter of the model. The results obtained are satisfactory.

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2007 IEEE Intelligent Vehicles Symposium

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