Real-time Pedestrian Detection in Urban Scenarios

被引:0
|
作者
Varga, Robert [1 ]
Vesa, Andreea Valeria [1 ]
Jeong, Pangyu [1 ]
Nedevschi, Sergiu [1 ]
机构
[1] Tech Univ Cluj Napoca, Cluj Napoca, Romania
来源
2014 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING (ICCP) | 2014年
关键词
Pedestrian detection; object recognition; region of interest selection; mobile devices; ORIENTED GRADIENTS; HISTOGRAMS;
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
A real-time pedestrian detection system is presented that runs at 24 fps on standard VGA resolution input images (640x480px) using only CPU processing. The detection algorithm uses a variable sized sliding window and intelligent simplifications such as a sparse scale space and fast candidate selection to obtain the desired speed. Details are provided about the initial version of the system ported on a mobile device. We also present a new labeled pedestrian dataset that was captured from a moving car that is suitable for training and testing pedestrian detection methods in urban scenarios.
引用
收藏
页码:113 / 118
页数:6
相关论文
共 50 条
  • [21] A robust system for real-time pedestrian detection and tracking
    Qi Li
    Chun-fu Shao
    Yi Zhao
    Journal of Central South University, 2014, 21 : 1643 - 1653
  • [22] Aggregated Channels Network for Real-Time Pedestrian Detection
    Ghorban, Farzin
    Marin, Javier
    Su, Yu
    Colombo, Alessandro
    Kummert, Anton
    TENTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2017), 2018, 10696
  • [23] Real-time pedestrian detection with deep supervision in the wild
    Li, Zhaoqing
    Chen, Zhenxue
    Wu, Q. M. Jonathan
    Liu, Chengyun
    SIGNAL IMAGE AND VIDEO PROCESSING, 2019, 13 (04) : 761 - 769
  • [24] Real-time pedestrian detection with deep supervision in the wild
    Zhaoqing Li
    Zhenxue Chen
    Q. M. Jonathan Wu
    Chengyun Liu
    Signal, Image and Video Processing, 2019, 13 : 761 - 769
  • [25] Close to real-time robust pedestrian detection and tracking
    Lipetski, Y.
    Loibner, G.
    Sidla, O.
    VIDEO SURVEILLANCE AND TRANSPORTATION IMAGING APPLICATIONS 2015, 2015, 9407
  • [26] EfficientLiteDet: a real-time pedestrian and vehicle detection algorithm
    Murthy, Chintakindi Balaram
    Hashmi, Mohammad Farukh
    Keskar, Avinash G.
    MACHINE VISION AND APPLICATIONS, 2022, 33 (03)
  • [27] Robust real-time pedestrian detection in surveillance videos
    Domonkos Varga
    Tamás Szirányi
    Journal of Ambient Intelligence and Humanized Computing, 2017, 8 : 79 - 85
  • [28] Real-time Pedestrian Detection with Deformable Part Models
    Cho, Hyunggi
    Rybski, Paul E.
    Bar-Hillel, Aharon
    Zhang, Wende
    2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), 2012, : 1035 - 1042
  • [29] Robust real-time pedestrian detection in surveillance videos
    Varga, Domonkos
    Sziranyi, Tamas
    JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 2017, 8 (01) : 79 - 85
  • [30] Hardware implementation of real-time pedestrian detection system
    Helali, Abdelhamid
    Ameur, Haythem
    Gorriz, J. M.
    Ramirez, J.
    Maaref, Hassen
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (16): : 12859 - 12871