A Two-Stage Object Tracking Method Based on Curvelet Transform and Mean Shift Algorithm

被引：0
|
作者：
Han, Pengcheng [1 ]
Du, Junping [1 ]
Li, Qingping [1 ]
Fang, Ming [1 ]
Yang, Yuehua [1 ]
Jia, Yingmin
机构：
[1] Beijing Univ Posts & Telecommun, Sch Comp Sci, Beijing Key Lab Intelligent Telecommun Software &, Beijing 100876, Peoples R China
来源：
2013 IEEE INTERNATIONAL SYMPOSIUM ON INDUSTRIAL ELECTRONICS (ISIE) | 2013年
关键词：
object tracking; Curvelet transform; translation Invariant; mean shift;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Traditional mean shift tracking algorithm couldn't track moving objects in cross-scale domain. In this paper, we propose a new two-stage object tracking method combined Curvelet Transform and mean shift algorithm. Our proposed method extracts image features using Curvelet transform, and calculates object location by cross-scale mean shift algorithm. The experimental results demonstrate that the proposed algorithm can effectively track moving objects. Compared with traditional mean shift algorithm, tracking accuracy has been significantly improved.
引用
收藏
页数：5
相关论文
共 50 条
  • [1] Object tracking approach based on mean shift algorithm
    Zhang, Xiaojing
    Yue, Yajie
    Sha, Chenming
    Journal of Multimedia, 2013, 8 (03): : 220 - 225
  • [2] A Novel Two-Stage PCA Algorithm for Object Tracking
    Yang, Yuanyuan
    Hu, Dong
    PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, INFORMATION MANAGEMENT AND NETWORK SECURITY, 2016, 47 : 289 - 292
  • [3] Mean Shift Algorithm in Object Tracking
    Wang, Juan
    Tao, Weiwei
    Zhao, Yizhi
    2012 THIRD INTERNATIONAL CONFERENCE ON THEORETICAL AND MATHEMATICAL FOUNDATIONS OF COMPUTER SCIENCE (ICTMF 2012), 2013, 38 : 270 - 275
  • [4] Two-Stage Object Tracking Method Based on Kernel and Active Contour
    Chen, Qiang
    Sun, Quan-Sen
    Heng, Pheng Ann
    Xia, De-Shen
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2010, 20 (04) : 605 - 609
  • [5] Two-stage object tracking method based on Siamese neural network
    Zhang H.
    Li X.
    Zhu B.
    Zhang Y.
    Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering, 2021, 50 (09):
  • [6] A mean shift object tracking algorithm based on covariance estimation
    Xiao, Jinsheng
    Zhang, Yaqi
    Shan, Shanshan
    Peng, Hong
    Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology), 2013, 44 (03): : 1049 - 1053
  • [7] Improved Multi-object Detection and Tracking Method Based on Mean Shift Algorithm
    Li Jian-qiang
    Lu Hao-bo
    Du Wen-feng
    INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, 2011, 14 (03): : 1075 - 1080
  • [8] Improved mean shift algorithm for object tracking
    School of Computer Science and Technology, Heilongjiang University, Harbin 150080, China
    Zidonghua Xuebao, 2007, 4 (347-354): : 347 - 354
  • [9] Hierarchical mean shift algorithm for object tracking
    School of Electrical and Information Engineering, Hunan University, Changsha 410082, China
    不详
    Zidonghua Xuebao Acta Auto. Sin., 2009, 4 (401-409): : 401 - 409
  • [10] Moving object tracking algorithm based on object estimation and Mean Shift theory
    Zhao, Qian
    Yuan, Jian-Quan
    Lu, Xin-Ping
    Li, Ji-Cheng
    Hongwai yu Jiguang Gongcheng/Infrared and Laser Engineering, 2010, 39 (06): : 1152 - 1156
12345