Building a Robust Appearance Model for Object Tracking

被引：1
|
作者：
Yao, Zhijun [1 ]
Feng, Bin [1 ]
Wang, Junwei [1 ]
Liu, Wenyu [1 ]
机构：
[1] Huazhong Univ Sci & Technol, Elect & Informat Engn Dept, Wuhan 430074, Peoples R China
来源：
2009 INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE AND COMPUTATIONAL INTELLIGENCE, VOL III, PROCEEDINGS | 2009年
关键词：
Computer Vision; Gaussian Mixture Model; Feature Extraction; CAMSHIFT; Object Tracking;
D O I：
10.1109/AICI.2009.165
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
One of the challenges to creating robust trackers is the construction of robust appearance Model. This paper presents a robust appearance model for object tracking. The robust object distribution is acquired by comparing the two Gaussian Mixture Models of the object and background. The probability image generated by the robust object distribution is used for the CAMSHIFT tracking. Experiments on several video sequences show the effectiveness of the proposed method.
引用
收藏
页码：471 / 475
页数：5
相关论文
共 50 条
  • [1] A Robust Appearance Model for Object Tracking
    Li, Yi
    Lu, Xiaohuan
    He, Zhenyu
    Wang, Hongpeng
    Chen, Wen-Sheng
    [J]. 2016 7TH INTERNATIONAL CONFERENCE ON CLOUD COMPUTING AND BIG DATA (CCBD), 2016, : 248 - 253
  • [2] A BAYESIAN HIERARCHICAL APPEARANCE MODEL FOR ROBUST OBJECT TRACKING
    Almomani, Rued
    Dong, Ming
    Zhu, Dongxiao
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA & EXPO (ICME), 2016,
  • [3] Learning online structural appearance model for robust object tracking
    YANG Min
    PEI MingTao
    WU YuWei
    JIA YunDe
    [J]. Science China(Information Sciences), 2015, 58 (03) : 105 - 118
  • [4] Learning online structural appearance model for robust object tracking
    Yang Min
    Pei MingTao
    Wu YuWei
    Jia YunDe
    [J]. SCIENCE CHINA-INFORMATION SCIENCES, 2015, 58 (03) : 1 - 14
  • [5] Robust Object Tracking via Sparse Collaborative Appearance Model
    Zhong, Wei
    Lu, Huchuan
    Yang, Ming-Hsuan
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2014, 23 (05) : 2356 - 2368
  • [6] Robust Object Tracking via Local Sparse Appearance Model
    Nai, Ke
    Li, Zhiyong
    Li, Guiji
    Wang, Shanquan
    [J]. IEEE TRANSACTIONS ON IMAGE PROCESSING, 2018, 27 (10) : 4958 - 4970
  • [7] Robust object tracking using sparse color appearance model
    Yang, Wenguang
    Luo, Zijuan
    Ren, Kan
    Wan, Minjie
    Qian, Ye
    Xu, Yunkai
    Qian, Weixian
    [J]. JOURNAL OF ELECTRONIC IMAGING, 2021, 30 (06)
  • [8] A hybrid motion and appearance prediction model for robust visual object tracking
    Jahandide, Hamidreza
    Mohamedpour, Kamal
    Moghaddam, Hamid Abrishami
    [J]. PATTERN RECOGNITION LETTERS, 2012, 33 (16) : 2192 - 2197
  • [9] Robust object tracking based on local region sparse appearance model
    Han, Guang
    Wang, Xingyue
    Liu, Jixin
    Sun, Ning
    Wang, Cailing
    [J]. NEUROCOMPUTING, 2016, 184 : 145 - 167
  • [10] Partial occlusion robust object tracking using an effective appearance model
    Zhang, Shengping
    Yao, Hongxun
    Liu, Shaohui
    [J]. VISUAL COMMUNICATIONS AND IMAGE PROCESSING 2010, 2010, 7744
12345