Focusing on Discrimination Between Road Conditions and Weather in Driving Video Analysis

被引：0

作者：

Zhang, Hanwei ^{[1
]}

Kawasaki, Hiroshi ^{[2
]}

Mine, Tsunenori ^{[2
]}

Ono, Shintaro ^{[3
]}

机构：

[1] Kyushu Univ, Grad Sch Informat Sci & Elect Engn, Fukuoka, Japan

[2] Kyushu Univ, Fac Informat Sci & Elect Engn, Fukuoka, Japan

[3] Univ Tokyo, Inst Ind Sci, Tokyo, Japan

来源：

FRONTIERS OF COMPUTER VISION, IW-FCV 2021 | 2021年 / 1405卷

关键词：

Driving video; Road condition; Weather classification; Deep learning;

D O I：

10.1007/978-3-030-81638-4_6

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We study an often ignored problem, the discrimination between road conditions and weather in driving videos, which may possibly lead to imperceptible errors on driving data analysis. We explore BDD100K, a common driving video database, and Kyushu Driving Data, a huge driving database created by ourselves. In our experiments, we use road condition labels and weather labels respectively to train several deep models on driving image sequences and demonstrate the difference between the two varieties of labels. The results indicate a significant difference between the two varieties, which leads to different performance of deep models.

引用

页码：70 / 80

页数：11

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