Monocular Vision based Road Marking Recognition for Driver Assistance and Safety

被引：0

作者：

Sukhwani, Mohak ^{[1
]}

Singh, Suriya ^{[1
]}

Goyal, Anirudh ^{[1
]}

Behl, Aseem ^{[1
]}

Mohapatra, Pritish ^{[1
]}

Bharti, Brijendra Kumar ^{[2
]}

Jawahar, C. V. ^{[1
]}

机构：

[1] IIIT Hyderabad, CVIT, Hyderabad, Andhra Pradesh, India

[2] RNTBCI, Madras, Tamil Nadu, India

来源：

2014 IEEE INTERNATIONAL CONFERENCE ON VEHICULAR ELECTRONICS AND SAFETY (ICVES) | 2014年

关键词：

Computer Vision; Road Marking Recognition; Driver Assistance; Vehicular Safety;

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：

In this paper, we present a solution to generate semantically richer descriptions and instructions for driver assistance and safety. Our solution builds upon a set of computer vision and machine learning modules. We start with low-level image processing and finally generate high-level descriptions. We do this by combining the results of the image pattern recognition module with the prior knowledge on traffic rules and larger context present in the video sequence. For recognition of road markings, we use a SVM based classifier and HOG based classifier. We test our method on real data captured in urban settings, and report impressive performance. Qualitative and quantitative performance of various modules are presented.

引用

页码：11 / 16

页数：6

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