Detection System of Truck Blind Area based on Machine Vision

被引：0

作者：

Ding, Wenjing ^{[1
]}

Zhang, Yang ^{[2
]}

Bu, Yang ^{[2
]}

Lu, Yilin ^{[2
]}

Zhu, Xia ^{[2
]}

机构：

[1] Jinling Inst Technol, Int Educ Coll, Nanjing, Peoples R China

[2] Jinling Inst Technol, Sch Networks & Telecommun Engn, Nanjing, Peoples R China

来源：

IWCMC 2021: 2021 17TH INTERNATIONAL WIRELESS COMMUNICATIONS & MOBILE COMPUTING CONFERENCE (IWCMC) | 2021年

关键词：

Truck blind area early warning system; Machine vision; Pedestrian detection; Target detection algorithm; Deep learning;

D O I：

10.1109/IWCMC51323.2021.9498867

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the continuous development of cargo transport, road transport has become an indispensable part of the logistics industry today. Because of the multi-directional visual blind area of freight cars, drivers cannot fully observe the surrounding environment, which is prone to traffic accidents. Therefore, it is of great significance to develop a reliable and safe detection system for truck blind area for road vehicle traffic safety. In this paper, based on the machine vision technology and combined with the scientific research project, the gradient distribution of local area is extracted by HOG feature, so as to realize the detection of the accuracy and rapidity of the detection of the blind area of trucks from multiple angles and in all aspects, and timely alarm is given to provide real driving convenience for truck drivers and provide higher safety guarantee for highway traffic.

引用

页码：2086 / 2089

页数：4

共 10 条

[1]

Chen Jiahao, 2017, CHINA PUBLIC SECURIT

[2]

Feng Gao, 2019, DISCUSSION DEV APPL

[3]

Liu Haiyang, 2017, RES BLIND AREA VEHIC

[4]

Liu Yuxi, 2017, RES TARGET RECOGNITI, P4

[5]

Sun Wei, 2014, RES CAUSATION MECH C

[6]

Wu Hongshan, 2018, INTERNAL COMBUSTION, P7

[7]

Yang Sisi, 2015, RES IMPLEMENTATION V

[8]

Yuan Jianjiang, 2017, INTELLIGENT COMPUTER, P12

[9]

Zhang Xinyu, J TSINGHUA

[10]

Zhao Zhicheng, 2018, AUTOMOTIVE ELECT, P2

← 1 →