On-road vehicle detection using optical sensors: A review

被引:0
|
作者
Sun, ZH [1 ]
Bebis, G [1 ]
Miller, R [1 ]
机构
[1] eTreppid Technol LLC, Reno, NV USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
As one of the most promising applications of computer vision, vision-based vehicle detection for driver assistance has received considerable attention over the last 15 years. There are at least three reasons for the blooming research in this field: first, the startling losses both in human lives and finance caused by vehicle accidents; second, the availability of feasible technologies accumulated within the last 30 years of computer vision research; and third, the exponential growth of processor speed has paved the way for running computation-intensive video-processing algorithms even on a low-end PC in realtime. This paper provides a critical survey of recent vision-based on-road vehicle detection systems appeared in the literature (i.e., the cameras are mounted on the vehicle rather than being static such as in traffic/driveway monitoring systems).
引用
收藏
页码:585 / 590
页数:6
相关论文
共 50 条
  • [31] High-Performance On-Road Vehicle Detection in Monocular Images
    Gabb, Michael
    Loehlein, Otto
    Wagner, Raimar
    Westenberger, Antje
    Fritzsche, Martin
    Dietmayer, Klaus
    2013 16TH INTERNATIONAL IEEE CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS - (ITSC), 2013, : 336 - 341
  • [32] On-Road Vehicle Detection based on Color Segmentation and Tracking Using Harris-SIFT
    Zheng, Zhihui
    Wang, Bo
    MATERIALS SCIENCE AND INFORMATION TECHNOLOGY, PTS 1-8, 2012, 433-440 : 5334 - 5338
  • [33] Accurate On-Road Vehicle Detection with Deep Fully Convolutional Networks
    Jie, Zequn
    Lu, Wen Feng
    Tay, Eng Hock Francis
    MACHINE LEARNING AND DATA MINING IN PATTERN RECOGNITION (MLDM 2016), 2016, 9729 : 643 - 658
  • [34] On-Road Vehicle Detection and Tracking Based on Road Context and the Ambient Lighting Adaptive Framework
    Kim, Sam-Yong
    Oh, Se-Young
    INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY, 2008, 18 (5-6) : 283 - 295
  • [35] Novel On-Road Vehicle Detection System Using Multi-Stage Convolutional Neural Network
    Kim, Jisu
    Hong, Sungjun
    Kim, Euntai
    IEEE ACCESS, 2021, 9 : 94371 - 94385
  • [36] Vision-Based On-Road Nighttime Vehicle Detection and Tracking Using Improved HOG Features
    Zhang, Li
    Xu, Weiyue
    Shen, Cong
    Huang, Yingping
    SENSORS, 2024, 24 (05)
  • [37] Accuracy Improvement Method for Vehicle Detection Using Optical Sensors
    Kovavisaruch, L.
    Sanpechuda, T.
    Chinrungrueng, J.
    Sununtachaikul, U.
    Kittipiyakul, S.
    Samphanyuth, S.
    ITST: 2009 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORT SYSTEMS TELECOMMUNICATIONS, 2009, : 218 - 222
  • [38] A method of on-road vehicle detection based on comprehensive feature cascade of classifier
    Li, Xiao Le
    Xiao, De Gui
    Xin, Chen
    Zhu, Huan
    INFORMATION TECHNOLOGY AND COMPUTER APPLICATION ENGINEERING, 2014, : 389 - 393
  • [39] A Method for On-road Night-time Vehicle Headlight Detection and Tracking
    Juric, Darko
    Loncaric, Sven
    2014 INTERNATIONAL CONFERENCE ON CONNECTED VEHICLES AND EXPO (ICCVE), 2014, : 655 - 660
  • [40] Fast and accurate on-road vehicle detection based on color intensity segregation
    Sravan, Manne Sai
    Natarajan, Sudha
    Krishna, Eswar Sai
    Kailath, Binsu J.
    INTERNATIONAL CONFERENCE ON ROBOTICS AND SMART MANUFACTURING (ROSMA2018), 2018, 133 : 594 - 603