Computer Science

Computer Science ›› 2022, Vol. 49 ›› Issue (3): 152-162.doi: 10.11896/jsjkx.210200048

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Object Initialization in Multiple Object Tracking:A Review

WEN Cheng-yu1, FANG Wei-dong2, CHEN Wei1,2   

  1. 1 School of Computer Science and Technology,China University of Mining and Technology,Xuzhou,Jiangsu 221116,China
    2 Key Laboratory of Wireless Sensor Network & Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences,Shanghai 200050,China
  • Received:2021-02-04 Revised:2021-06-03 Online:2022-03-15 Published:2022-03-15
  • About author:WEN Cheng-yu,born in 1995,postgra-duate.His main research interests include machine learning and image processing.
    CHEN Wei,born in 1978,Ph.D,professor,is a member of IEEE.His main research interests include machine lear-ning,image processing,and computer networks.
  • Supported by:
    National Natural Science Foundation of China(51874300),National Natural Science Foundation of China and Shanxi Provincial People’s Government Jointly Funded Project of China for Coal Base and Low Carbon(U1510115) and Open Research Fund of Key Laboratory of Wireless Sensor Network & Communication,Shanghai Institute of Microsystem and Information Technology,Chinese Academy of Sciences(20190902,20190913).

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Abstract: Object initialization method determines how to treat the multi-object tracking problem,being directly related to the subsequent tracking result.Different object initialization methods confirm different multi-object tracking frameworks and each framework provides a way to solve the problem,which makes the object initialization of multi-object tracking a huge research prospect.Currently there are few literature on object initialization methods of multi-target tracking,or lacks a systematic overview of object initialization.Therefore,we analyze the object initialization methods on four aspects:multi-hypothesis tracking,network flow,deep learning and topic discovery.We systematically expound the task conversion and object mapping problems under diffe-rent multi-object tracking frameworks,and summarize the object initialization methods for the multi-object tracking.

Key words: Deep learning, Multiple hypothesis tracking, Multiple target tracking, Network flow, Object initialization, Topic discovery

CLC Number: 

  • TP391
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