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
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] Object tracking based on Camshift with multi-feature fusion
    Zhou, Z. (zhouzhiyu1993@163.com), 1600, Academy Publisher (09):
  • [32] Infrared Target Tracking Using Multi-Feature Joint Sparse Representation
    Gao, Shu Juan
    Jhang, Seong Tae
    2016 RESEARCH IN ADAPTIVE AND CONVERGENT SYSTEMS, 2016, : 40 - 45
  • [33] Multi-feature Fusion Based Object Detecting and Tracking
    Lu, Hong
    Li, Hongsheng
    Chai, Lin
    Fei, Shumin
    Liu, Guangyun
    MATERIALS AND COMPUTATIONAL MECHANICS, PTS 1-3, 2012, 117-119 : 1824 - +
  • [34] Multi-feature fusion dynamic target tracking algorithm for complex scenes
    Cheng, Jian
    Chen, Liang
    Wang, Kai
    Guo, Yinan
    Yan, Pengpeng
    Zhongguo Kuangye Daxue Xuebao/Journal of China University of Mining and Technology, 2021, 50 (05): : 1002 - 1010
  • [35] Multi-feature graph-based object tracking
    Taj, Murtaza
    Maggio, Emilio
    Cavallaro, Andrea
    MULTIMODAL TECHNOLOGIES FOR PERCEPTION OF HUMANS, 2007, 4122 : 190 - 199
  • [36] Accelerated multi-feature based compressive sensing tracking
    He, Liang
    Bo, Yuming
    Zhao, Gaopeng
    INFRARED PHYSICS & TECHNOLOGY, 2015, 71 : 424 - 431
  • [37] Vehicle tracking based on multi-feature adaptive fusion
    School of Electric Engineering and Information Engineering, Lanzhou University of Technology, Lanzhou 730050, China
    不详
    Nongye Jixie Xuebao, 2013, 4 (33-38):
  • [38] High-speed Target Tracking base on FPGA
    Lyu, Congyi
    Liu, Yunhui
    Zhou, Weiguo
    Peng, Jianging
    Yang, Shanshan
    Zhang, Huijun
    Yang, Linsen
    2016 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE RCAR), 2016, : 272 - 276
  • [39] Improved Particle filtering algorithm based on the multi-feature fusion for small IR target tracking
    Ji Er-you
    Gu Guo-hua
    Qian Wei-xian
    Bai Lian-fa
    Sui Xiu-bao
    INTERNATIONAL SYMPOSIUM ON PHOTOELECTRONIC DETECTION AND IMAGING 2011: ADVANCES IN INFRARED IMAGING AND APPLICATIONS, 2011, 8193
  • [40] Multi-feature Based Ensemble Classification and Regression Tree (ECART) for Target Tracking in Infrared Imagery
    Hu, Tun
    Liu, Erqi
    Yang, Jie
    JOURNAL OF INFRARED MILLIMETER AND TERAHERTZ WAVES, 2009, 30 (05) : 484 - 495