Vehicle Color Recognition in The Surveillance with Deep Convolutional Neural Networks

被引：0

作者：

Su, Boyang ^{[1
]}

Shao, Jie ^{[1
]}

Zhou, Jianying ^{[1
]}

Zhang, Xiaoteng ^{[1
]}

Mei, Lin ^{[1
]}

机构：

[1] Minist Publ Secur, Res Inst 3, Internet Things Technol Dept, Shanghai, Peoples R China

来源：

PROCEEDINGS OF THE 2015 JOINT INTERNATIONAL MECHANICAL, ELECTRONIC AND INFORMATION TECHNOLOGY CONFERENCE (JIMET 2015) | 2015年 / 10卷

关键词：

Vehicle Color Recognition; Deep Convolutional Nerual Networks; network in network;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Vehicle information extraction is the key means in Intelligent Transportation System ( ITS). Color plays an important role in vehicle recognition. The main challenge of vehicle color recognition is to find the dominant color. In this paper, we propose a color recognition method using convolutional neural network. We train the classifier with the network structure 'NIN' to increase the classification accuracy. The experiments are validated on our dataset and extra data, which are collected from city surveillance equipment. The proposed method outperforms other competing color recognition methods.

引用

页码：790 / 793

页数：4

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