Visibility estimation in foggy conditions by in-vehicle camera and radar

被引:0
|
作者
Mori, Kenji [1 ]
Kato, Terutoshi [1 ]
Takahashi, Tomokazu [1 ]
Ide, Ichiro [1 ]
Murase, Hiroshi [1 ]
Miyahara, Takayuki [2 ]
Tamatsu, Yukimasa [2 ]
机构
[1] Nagoya Univ, Grad Sch Informat Sci, Chikusa Ku, Furo Cho, Nagoya, Aichi 4648603, Japan
[2] DENSO CORP, Aichi, Japan
关键词
fog; visibility; in-vehicle camera;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We propose a method of judging fog density by using in-vehicle camera images and millimeter-wave (mm-W) radar data. This method determines fog density by evaluating both the visibility of a preceding vehicle and the distance to it. Experiments revealed that judgments made by the proposed method achieved an 85% precision rate compared to that made by human subjects.
引用
收藏
页码:548 / +
页数:2
相关论文
共 50 条
  • [1] Recognition of foggy conditions by in-vehicle camera and millimeter wave radar
    Mori, Kenji
    Takahashi, Tomokazu
    Ide, Ichiro
    Murase, Hiroshi
    Miyahara, Takayuki
    Tamatsu, Yukirnasa
    2007 IEEE INTELLIGENT VEHICLES SYMPOSIUM, VOLS 1-3, 2007, : 429 - +
  • [2] A Kalman filter based restoration method for in-vehicle camera images in foggy conditions
    Hiramatsu, Tomoki
    Ogawa, Takahiro
    Haseyama, Miki
    2008 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING, VOLS 1-12, 2008, : 1245 - 1248
  • [3] Vehicle Speed Estimation by In-Vehicle Camera
    Kaneko, Hiroki
    Morimoto, Masakazu
    Fujii, Kensaku
    2012 WORLD AUTOMATION CONGRESS (WAC), 2012,
  • [4] A Kalman Filter-Based Method for Restoration of Images Obtained by an In-Vehicle Camera in Foggy Conditions
    Hiramatsu, Tomoki
    Ogawa, Takahiro
    Haseyama, Miki
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2009, E92A (02) : 577 - 584
  • [5] DHCNN for Visibility Estimation in Foggy Weather Conditions
    o'g'li, Palvanov Akmaljon Alijon
    Cho, Young Im
    2018 JOINT 10TH INTERNATIONAL CONFERENCE ON SOFT COMPUTING AND INTELLIGENT SYSTEMS (SCIS) AND 19TH INTERNATIONAL SYMPOSIUM ON ADVANCED INTELLIGENT SYSTEMS (ISIS), 2018, : 240 - 243
  • [6] Improve Visibility of Nighttime Images for Pedestrian Recognition by In-Vehicle Camera
    Ogura, Ryota
    Nagasaki, Takeshi
    2018 IEEE 7TH GLOBAL CONFERENCE ON CONSUMER ELECTRONICS (GCCE 2018), 2018, : 51 - 54
  • [7] Deep Camera-Radar Fusion with an Attention Framework for Autonomous Vehicle Vision in Foggy Weather Conditions
    Ogunrinde, Isaac
    Bernadin, Shonda
    SENSORS, 2023, 23 (14)
  • [8] A KALMAN FILTER-BASED APPROACH FOR ADAPTIVE RESTORATION OF IN-VEHICLE CAMERA FOGGY IMAGES
    Hiramatsu, Tomoki
    Ogawa, Takahiro
    Haseyama, Miki
    2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5, 2008, : 3160 - 3163
  • [9] Improving the visibility of nighttime images for pedestrian recognition using in-vehicle camera
    Ogura, Ryota
    Nagasaki, Takeshi
    Matsubara, Hitoshi
    ELECTRONICS AND COMMUNICATIONS IN JAPAN, 2020, 103 (10) : 35 - 43
  • [10] 4D Radar-Camera Sensor Fusion for Robust Vehicle Pose Estimation in Foggy Environments
    Yang, Seunghoon
    Choi, Minseong
    Han, Seungho
    Choi, Keun-Ha
    Kim, Kyung-Soo
    IEEE Access, 2024, 12 : 16178 - 16188