Multi-feature Based High-speed Ball Shape Target Tracking

被引:0
|
作者
Lyu, Congyi [1 ,2 ]
Liu, Yunhui [2 ]
Li, Bing [3 ]
Chen, Haoyao [3 ]
机构
[1] Beijing Inst Technol, Sch Mechatron Engn, Beijing 100081, Peoples R China
[2] Chinese Univ Hong Kong, Dept Mech & Automat Engn, Hong Kong, Hong Kong, Peoples R China
[3] Harbin Inst Technol, Shenzhen Grad Sch, Shenzhen 518055, Peoples R China
来源
2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION | 2015年
关键词
Ball shape target; Contour; Hu-moment; Multi-feature; ROI control;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Ball shape object tracking is very important in sports video analysis such as tennis, golf ball and basketball. In this paper, a real-time high speed moving ball shape object tracking algorithm based on frame difference and multi-feature fusion is proposed. First of all, it detects the frame difference between the adjacent two frames. Then it divides the difference image into several small contours and decides if they are moving ball shape object areas by multi-feature based algorithm. It labelled the ball shape object and the smallest rectangle ROI (Region Of Interesting) which contains the moving object. At last, according to the location and size of ROI, intelligently control the size and location of CMOS image senor's ROI. We also proposed a system to implement and validate the proposed algorithm in a wireless pan-tilt camera system. Experimental results show that the algorithm can be applied to real-time tracking of ball shape object with a high recognition rate, and the ROI control method can enhance the processing efficiency.
引用
收藏
页码:67 / 72
页数:6
相关论文
共 50 条
  • [31] A Novel Wipe Transition Detection Method Based on Multi-Feature
    Li Yufeng
    Yang Yinghua
    Li Guiju
    THIRD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING: WKDD 2010, PROCEEDINGS, 2010, : 451 - 454
  • [32] A Multi-feature Fusion Based Method For Urban Sound Tagging
    Bai, Jisheng
    Chen, Chen
    Chen, Jianfeng
    2019 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2019, : 1313 - 1317
  • [33] Unifying Temporal Context and Multi-Feature With Update-Pacing Framework for Visual Tracking
    Gao, Yuefang
    Hu, Zexi
    Yeung, Henry Wing Fung
    Chung, Yuk Ying
    Tian, Xuhong
    Lin, Liang
    IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY, 2020, 30 (04) : 1078 - 1091
  • [34] Multi-Modal Image Registration Based on Multi-Feature Mutual Information
    Liu, Xueli
    Wang, Manning
    Song, Zhijian
    JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2019, 9 (01) : 153 - 158
  • [35] Study on the technology of classifying high-resolution remote sensing image based on multi-feature
    Lin, H
    Li, JP
    Mo, DK
    Xiong, YJ
    Sun, H
    Liu, XY
    REMOTE SENSING AND SPACE TECHNOLOGY FOR MULTIDISCIPLINARY RESEARCH AND APPLICATIONS, 2006, 6199
  • [36] Multi-Feature Classification Approach for High Spatial Resolution Hyperspectral Images
    Tan, Yumin
    Xia, Wei
    Xu, Bo
    Bai, Linjie
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2018, 46 (01) : 9 - 17
  • [37] Multi-Feature Classification Approach for High Spatial Resolution Hyperspectral Images
    Yumin Tan
    Wei Xia
    Bo Xu
    Linjie Bai
    Journal of the Indian Society of Remote Sensing, 2018, 46 : 9 - 17
  • [38] Multi-feature fusion friend recommendation algorithm based on complex network
    Pan K.
    Chen H.
    Liu Q.
    Wang J.
    Pu Y.
    Yin C.
    Yang Z.
    Zhao N.
    International Journal of Information and Communication Technology, 2023, 23 (04) : 401 - 423
  • [39] Optimized Method of Multi-Feature for Content-based Image Retrieval
    Dai, Zhengyan
    Qin, Sujuan
    PROCEEDINGS OF THE 3RD INTERNATIONAL CONFERENCE ON MECHATRONICS AND INDUSTRIAL INFORMATICS, 2015, 31 : 864 - 869
  • [40] Detection of Pecan Quality Based on Multi-feature Fusion and Level Set
    Liu Z.
    Zou X.
    Song Y.
    Wang M.
    Su J.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50 (12): : 348 - 356and364