Moving target detection approach based on spatio-temporal salient perception

被引:1
|
作者
Jin, Gang [1 ]
Li, Zhengzhou [2 ,3 ]
Gu, Yuanshan [2 ]
Li, Jialing [2 ]
Cao, Dong [1 ]
Liu, Linyan [1 ]
机构
[1] China Aerodynam Res & Dev Ctr, Mianyang 621000, Peoples R China
[2] Chongqing Univ, Coll Commun Engn, Chongqing 400030, Peoples R China
[3] Chinese Acad Sci, Key Lab Beam Control, Chengdu 610209, Peoples R China
来源
OPTIK | 2014年 / 125卷 / 22期
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
Moving target detection; Spatial salient maps; Motion salient map; Spatio-temporal salient map; VISUAL-ATTENTION; MODEL; RECOGNITION; TRANSFORM; OBJECT; MOTION; SHIFTS;
D O I
10.1016/j.ijleo.2014.08.051
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
The differences in texture and motion between man-made object and natural scene are the key features for human biological visual system to detect moving object in scenery. The paper proposed a moving target detection approach based on spatio-temporal perception, which is a crucial function of the visual attention mechanism. The spatial feature including edge, orientation, texture and contrast of the image are extracted, and then the corresponding spatial salient map are constructed by fusing the features through difference of Gaussian (DOG) function, which can suppress the common and enhance the difference of local region. Then, the global motion, local motion and relative motion between continuous images are extracted by means of pyramid multi-resolution, and the moving salient map is constructed after the motion difference between moving target and background is confirmed. Finally, the spatio-temporal salient map is constructed by fusing the spatial salient map and the moving salient map through competition strategy, and the moving target could be detected by searching the maximum in the spatio-temporal salient map. Some experiments are included and the results show that the method can accurately detect the moving target in complex background. (C) 2014 Elsevier GmbH. All rights reserved.
引用
收藏
页码:6681 / 6686
页数:6
相关论文
共 50 条
  • [41] Abnormal event detection in tourism video based on salient spatio-temporal features and sparse combination learning
    Yue Geng
    Junping Du
    Meiyu Liang
    [J]. World Wide Web, 2019, 22 : 689 - 715
  • [42] Abnormal event detection in tourism video based on salient spatio-temporal features and sparse combination learning
    Geng, Yue
    Du, Junping
    Liang, Meiyu
    [J]. WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2019, 22 (02): : 689 - 715
  • [43] Event Detection using Twitter: A Spatio-Temporal Approach
    Cheng, Tao
    Wicks, Thomas
    [J]. PLOS ONE, 2014, 9 (06):
  • [44] Video Identification Using Spatio-temporal Salient Points
    Li, Yue-nan
    Lu, Zhe-ming
    [J]. FIFTH INTERNATIONAL CONFERENCE ON INFORMATION ASSURANCE AND SECURITY, VOL 2, PROCEEDINGS, 2009, : 79 - 82
  • [45] Spatio-temporal dynamics of face perception
    Muukkonen, I
    Olander, K.
    Numminen, J.
    Salmela, V. R.
    [J]. NEUROIMAGE, 2020, 209
  • [46] An Efficient and Agile Spatio-temporal Route Mutation Moving Target Defense Mechanism
    Zhou, Zan
    Xu, Changqiao
    Kuang, Xiaohui
    Zhang, Tao
    Sun, Limin
    [J]. ICC 2019 - 2019 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC), 2019,
  • [47] The study on the spatio-temporal model of the moving objects based on LBS
    Zhou, Li
    Zhang, Deli
    He, Xuezhao
    [J]. GEOINFORMATICS 2007: GEOSPATIAL INFORMATION TECHNOLOGY AND APPLICATIONS, PTS 1 AND 2, 2007, 6754
  • [48] Boundary extraction of moving object based on spatio-temporal information
    Mao, Ling
    Xie, Mei
    Li, Jia
    [J]. 2007 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, CIRCUITS AND SYSTEMS PROCEEDINGS, VOLS 1 AND 2: VOL 1: COMMUNICATION THEORY AND SYSTEMS; VOL 2: SIGNAL PROCESSING, COMPUTATIONAL INTELLIGENCE, CIRCUITS AND SYSTEMS, 2007, : 796 - +
  • [49] Trajectory Modeling of Moving Objects Based in Spatio-temporal Database
    Liu Jun
    Li Jingwei
    [J]. ADVANCED MATERIALS SCIENCE AND TECHNOLOGY, PTS 1-2, 2011, 181-182 : 54 - 59
  • [50] Spatio-Temporal Analysis for Moving Object Detection Under Complex Environment
    Suheryadi, Adi
    Nugroho, Hertog
    [J]. 2016 INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER SCIENCE AND INFORMATION SYSTEMS (ICACSIS), 2016, : 498 - 504