CDT: Cooperative detection and tracking for tracing multiple objects in video sequences

Han Ul Kim, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

29 Citations (Scopus)


A cooperative detection and model-free tracking algorithm, referred to as CDT, for multiple object tracking is proposed in this work. The proposed CDT algorithm has three components: object detector, forward tracker, and backward tracker. First, the object detector detects targets with high confidence levels only to reduce spurious detection and achieve a high precision rate. Then, each detected target is traced by the forward tracker and then by the backward tracker to restore undetected states. In the tracking processes, the object detector cooperates with the trackers to handle appearing or disappearing targets and to refine inaccurate state estimates. With this detection guidance, the model-free tracking can trace multiple objects reliably and accurately. Experimental results show that the proposed CDT algorithm provides excellent performance on a recent benchmark. Furthermore, an online version of the proposed algorithm also excels in the benchmark.

Original languageEnglish
Title of host publicationComputer Vision - 14th European Conference, ECCV 2016, Proceedings
EditorsBastian Leibe, Jiri Matas, Nicu Sebe, Max Welling
PublisherSpringer Verlag
Number of pages17
ISBN (Print)9783319464657
Publication statusPublished - 2016
Event14th European Conference on Computer Vision, ECCV 2016 - Amsterdam, Netherlands
Duration: 2016 Oct 82016 Oct 16

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9910 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference14th European Conference on Computer Vision, ECCV 2016

Bibliographical note

Funding Information:
This work was supported partly by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF- 2015R1A2A1 A10055037), and partly by the MSIP, Korea, under the ITRC support program supervised by the Institute for Information & communications Technology Promotion (No. IITP-2016-R2720-16-0007).

Publisher Copyright:
© Springer International Publishing AG 2016.

Copyright 2021 Elsevier B.V., All rights reserved.


  • Joint detection and tracking
  • Model-free tracking
  • Multiple object tracking
  • Object detection
  • Online multi-object tracking

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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