Image Segmentation-Based Bicycle Riding Side Identification Method

被引:3
作者
Kim, Jeyoen [1 ]
Soma, Takumi [2 ,3 ]
Manabe, Tetsuya [3 ]
Kojima, Aya [3 ]
机构
[1] Natl Inst Technol, Tsuruoka Coll, Dept Creat Engn, Tsuruoka 9978511, Japan
[2] Natl Inst Technol, Tsuruoka Coll, Adv Engn Course, Tsuruoka 9978511, Japan
[3] Saitama Univ, Grad Sch Sci & Engn, Saitama 3388570, Japan
关键词
bicycle riding side; image segmentation; advanced bicycle navigation system; bicycle riding safety support system;
D O I
10.1587/transfun.2022WBP0003
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
This paper attempts to identify which side of the road a bicycle is currently riding on using a common camera for realizing an ad-vanced bicycle navigation system and bicycle riding safety support system. To identify the roadway area, the proposed method performs semantic seg-mentation on a front camera image captured by a bicycle drive recorder or smartphone. If the roadway area extends from the center of the image to the right, the bicyclist is riding on the left side of the roadway (i.e., the correct riding position in Japan). In contrast, if the roadway area extends to the left, the bicyclist is on the right side of the roadway (i.e., the incorrect riding position in Japan). We evaluated the accuracy of the proposed method on various road widths with different traffic volumes using video captured by riding bicycles in Tsuruoka City, Yamagata Prefecture, and Saitama City, Saitama Prefecture, Japan. High accuracy (>80%) was achieved for any combination of the segmentation model, riding side identification method, and experimental conditions. Given these results, we believe that we have realized an effective image segmentation-based method to identify which side of the roadway a bicycle riding is on.
引用
收藏
页码:775 / 783
页数:9
相关论文
共 31 条
  • [11] Shadow Removal via Shadow Image Decomposition
    Le, Hieu
    Samaras, Dimitris
    [J]. 2019 IEEE/CVF INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV 2019), 2019, : 8577 - 8586
  • [12] VPGNet: Vanishing Point Guided Network for Lane and Road Marking Detection and Recognition
    Lee, Seokju
    Kim, Junsik
    Yoon, Jae Shin
    Shin, Seunghak
    Bailo, Oleksandr
    Kim, Namil
    Lee, Tae-Hee
    Hong, Hyun Seok
    Han, Seung-Hoon
    Kweon, In So
    [J]. 2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, : 1965 - 1973
  • [13] Deep Neural Network for Structural Prediction and Lane Detection in Traffic Scene
    Li, Jun
    Mei, Xue
    Prokhorov, Danil
    Tao, Dacheng
    [J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2017, 28 (03) : 690 - 703
  • [14] Effects of built environment on bicycle wrong Way riding behavior: A data -driven approach
    Luan, Sen
    Li, Meng
    Li, Xin
    Ma, Xiaolei
    [J]. ACCIDENT ANALYSIS AND PREVENTION, 2020, 144
  • [15] A Design Methodology Based on the Comprehensive Framework for Pedestrian Navigation Systems
    Manabe, Tetsuya
    Kojima, Aya
    [J]. IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2020, E103A (09) : 1111 - 1119
  • [16] Monteiro G, 2007, IEEE IMAGE PROC, P2393
  • [17] Morimoto M., 2014, J I IMAGE INF TELEV, V68, pJ47, DOI [10.3169/itej.68.J47, DOI 10.3169/ITEJ.68.J47]
  • [18] NAVITIME JAPAN Co. Ltd., BICYCLE NAVITIME
  • [19] Route Calculation for Bicycle Navigation System Following Traffic Rules
    Nawano, Taichi
    Manabe, Tetsuya
    [J]. IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2021, E104A (02) : 366 - 370
  • [20] Ooi M., 2016, PROC INT C MOB UBIQU, P75, DOI [10.1145/2994374.2994396, DOI 10.1145/2994374.2994396]