A visual nervous network for moving object recognition

被引:0
|
作者
Sato, N [1 ]
Hagiwara, M [1 ]
机构
[1] Keio Univ, Fac Sci & Technol, Dept Informat & Comp Sci, Kouhoku Ku, Yokohama, Kanagawa 2238522, Japan
关键词
visual sense; moving object recognition; walking human;
D O I
暂无
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we propose a visual nervous network for moving object recognition. This network is based on a visual nervous network which has a hierarchical parallel-structure. The network consists of three modules: the movement detection module, the moving object estimation module and the moving object recognition module. The movement detection module detects moving points and their direction. The moving object estimation module estimates the moving object on motion features. The moving object recognition module recognizes the moving object on its form feature. The network is able to recognize the moving object by uniting motion recognition and pattern recognition. We carried out computer simulations using real moving images to confirm the effectiveness of the proposed network.
引用
收藏
页码:2557 / 2562
页数:6
相关论文
共 50 条
  • [1] A visual neural network for moving object recognition
    Sato, N
    Hagiwara, M
    [J]. ELECTRONICS AND COMMUNICATIONS IN JAPAN PART II-ELECTRONICS, 2004, 87 (09): : 46 - 55
  • [2] A visual nervous system based multi-module neural network for object recognition
    Tannai, T
    Hagiwara, M
    [J]. 1998 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN, AND CYBERNETICS, VOLS 1-5, 1998, : 4284 - 4289
  • [3] Lightweight Network Model for Moving Object Recognition
    Fu H.
    Wang P.
    Li X.
    Lü Z.
    Di R.
    [J]. Hsi-An Chiao Tung Ta Hsueh/Journal of Xi'an Jiaotong University, 2021, 55 (07): : 124 - 131
  • [4] Moving Object Recognition for Airport Ground Surveillance Network
    Zhang, Zhizhuo
    Zhang, Xiang
    Chen, Donghang
    Yu, Haifei
    [J]. MOBILE NETWORKS AND MANAGEMENT, MONAMI 2021, 2022, 418 : 335 - 343
  • [5] Recognition of Moving Object in High Dynamic Scene for Visual Prosthesis
    Guo, Fei
    Yang, Yuan
    Xiao, Yang
    Gao, Yong
    Yu, Ningmei
    [J]. IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2019, E102D (07) : 1321 - 1331
  • [6] A Visual Sensor Network for Object Recognition: Testbed Realization
    Redondi, A.
    Baroffio, L.
    Canclini, A.
    Cesana, M.
    Tagliasacchi, M.
    [J]. 2013 18TH INTERNATIONAL CONFERENCE ON DIGITAL SIGNAL PROCESSING (DSP), 2013,
  • [7] Visual Attentional Network and Learning Method for Object Search and Recognition
    Lü J.
    Luo F.
    Yuan Z.
    [J]. Jixie Gongcheng Xuebao/Journal of Mechanical Engineering, 2019, 55 (11): : 123 - 130
  • [8] Beyond PARADISE:: Extensions to a neural network for visual object recognition
    France, I
    Duller, AWG
    [J]. INTERNATIONAL CONFERENCE ON ADVANCES IN PATTERN RECOGNITION, 1999, : 206 - 215
  • [9] A convolutional neural network for visual object recognition in marine sector
    Kumar, Aiswarya S.
    Sherly, Elizabeth
    [J]. 2017 2ND INTERNATIONAL CONFERENCE FOR CONVERGENCE IN TECHNOLOGY (I2CT), 2017, : 304 - 307
  • [10] Visual object recognition
    Logothetis, NK
    Sheinberg, DL
    [J]. ANNUAL REVIEW OF NEUROSCIENCE, 1996, 19 : 577 - 621