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

Hanwei Zhang, Hiroshi Kawasaki, Tsunenori Mine, Shintaro Ono

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

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.

Original languageEnglish
Title of host publicationFrontiers of Computer Vision - 27th International Workshop, IW-FCV 2021, Revised Selected Papers
EditorsHieyong Jeong, Kazuhiko Sumi
PublisherSpringer Science and Business Media Deutschland GmbH
Pages70-80
Number of pages11
ISBN (Print)9783030816377
DOIs
Publication statusPublished - 2021
Event27th International Workshop on Frontiers of Computer Vision, IW-FCV 2021 - Virtual, Online
Duration: Feb 22 2021Feb 23 2021

Publication series

NameCommunications in Computer and Information Science
Volume1405
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937

Conference

Conference27th International Workshop on Frontiers of Computer Vision, IW-FCV 2021
CityVirtual, Online
Period2/22/212/23/21

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Mathematics(all)

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