Context Enhanced Traffic Segmentation: traffic jam and road surface segmentation from aerial image

Yubo Wang, Zhao Wang, Yuusuke Nakano, Ken Nishimatsu, Katsuya Hasegawa, Jun Ohya

研究成果: Conference contribution

抄録

Traffic jam detection and density estimation of aerial images have been widely utilized in various scenarios, such as vehicle routing and city management. Rather than directly detecting traffic jams or estimating density, traffic condition analysis based on traffic jam segmentation could yield more accurate results. Therefore, we propose a Context Enhanced Traffic Segmentation Model to simultaneously segment the traffic jam parts and road surface. However, there are two critical issues for traffic jam segmentation in aerial images: one is the scale variation problem and the other is the difficulty of accurately segmenting ambiguous traffic jam boundaries. Thus, we design a traffic estimation module to handle the scale variation problem and present a context attention module to enhance the boundary of traffic jam segmentation. Experimental results demonstrate the superiority of our proposed method.

本文言語English
ホスト出版物のタイトルIVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781665478229
DOI
出版ステータスPublished - 2022
イベント14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2022 - Nafplio, Greece
継続期間: 2022 6月 262022 6月 29

出版物シリーズ

名前IVMSP 2022 - 2022 IEEE 14th Image, Video, and Multidimensional Signal Processing Workshop

Conference

Conference14th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2022
国/地域Greece
CityNafplio
Period22/6/2622/6/29

ASJC Scopus subject areas

  • コンピュータ ビジョンおよびパターン認識
  • 信号処理
  • メディア記述

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