Real-Time Vehicle and Pedestrian Detection Through SSD in Indian Traffic Conditions

被引:0
作者
Raj, Mayank [1 ]
Chandan, Swet [1 ]
机构
[1] Galgotias Univ, Dept Mech Engn, Greater Noida, India
来源
2018 INTERNATIONAL CONFERENCE ON COMPUTING, POWER AND COMMUNICATION TECHNOLOGIES (GUCON) | 2018年
关键词
SSD; CNN; convolutional layer; ANN; vehicle detection; Pedestrian detection; real-time; multi-box;
D O I
暂无
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Object detection is a standout amongst the most vital segment of self-driving cars. It is very challenging especially in the case of Indian roads which possess numerous issues including non-standard vehicles, unskilled drivers, lower visibility due to pollution and despicable path division. In this paper, we have to test our algorithm for Indian traffic conditions through Single Shot Multi-box Detection (SSD) method. For this, we have run our algorithm on the live feed video captured by the camera (30fps) for 25 km stretch and approximately 8000 image datasets on the Noida-Greater Noida Expressway. The implemented algorithm furnishes an accuracy of 96% with a high obvious positive rate of 94.23% and a minor false positive of 4%.
引用
收藏
页码:439 / 444
页数:6
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