Alerting the drivers about road signs with poor visual saliency

Ludovic Simon, Jean-Philippe Tarel, R. Brémond
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引用次数: 44

Abstract

This paper proposes an improvement of Advanced Driver Assistance System based on saliency estimation of road signs. After a road sign detection stage, its saliency is estimated using a SVM learning. A model of visual saliency linking the size of an object and a size-independent saliency is proposed. An eye tracking experiment in context close to driving proves that this computational evaluation of the saliency fits well with human perception, and demonstrates the applicability of the proposed estimator for improved ADAS.
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提醒司机注意视觉不明显的道路标志
本文提出了一种基于道路标志显著性估计的高级驾驶辅助系统改进方案。在道路标志检测阶段后,使用支持向量机学习估计其显著性。提出了一种将物体的大小与尺寸无关的显著性联系起来的视觉显著性模型。一个接近驾驶环境的眼动追踪实验证明了这种显著性的计算评估与人类感知非常吻合,并证明了所提出的估计器对改进的ADAS的适用性。
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