Detection and Recognition of Traffic Signs Inside the Attentional Visual Field of Drivers

被引：0

作者：

Zabihi, S. J. ^{[1
]}

Zabihi, S. M. ^{[1
]}

Beauchemin, S. S. ^{[1
]}

Bauer, M. A. ^{[1
]}

机构：

[1] Western Univ, Dept Comp Sci, London, ON N6A 5B7, Canada

来源：

2017 28TH IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV 2017) | 2017年

关键词：

FEATURES;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Traffic sign detection and recognition systems are essential components of Advanced Driver Assistance Systems and self-driving vehicles. In this contribution we present a vision-based framework which detects and recognizes traffic signs inside the attentional visual field of drivers. This technique takes advantage of the driver 3D absolute gaze point obtained through the combined use of a front-view stereo imaging system and a non-contact 3D gaze tracker. We used a linear Support Vector Machine as a classifier and a Histogram of Oriented Gradient as features for detection. Recognition is performed by using Scale Invariant Feature Transforms and color information. Our technique detects and recognizes signs which are in the field of view of the driver and also provides indication when one or more signs have been missed by the driver.

引用

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页码：583 / 588

页数：6

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