Robust online multi-object tracking by maximum a posteriori estimation with sequential trajectory prior

Min Yang*, Mingtao Pei, Jiajun Shen, Yunde Jia

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

This paper address the problem of online multi-object tracking by using the Maximum a Posteriori (MAP) framework. Given the observations up to the current frame, we estimate the optimal object trajectories by solving two MAP estimation problems: object detection and trajectory-detection association. By introducing the sequential trajectory prior, i.e., the prior information from previous frames about “good” trajectories, into MAP estimation, the output of the pre-trained object detector is refined and the correctness of the association between trajectories and detections is enhanced. In addition, the sequential trajectory prior allows the two MAP stages interact with each other in a sequential manner, which facilitates online multi-object tracking. Our experiments on publicly available challenging datasets demonstrate that the proposed algorithm provides superior performance in various complex scenes.

Original languageEnglish
Title of host publicationNeural Information Processing - 22nd International Conference, ICONIP 2015, Proceedings
EditorsWeng Kin Lai, Qingshan Liu, Tingwen Huang, Sabri Arik
PublisherSpringer Verlag
Pages623-633
Number of pages11
ISBN (Print)9783319265315
DOIs
Publication statusPublished - 2015
Event22nd International Conference on Neural Information Processing, ICONIP 2015 - Istanbul, Turkey
Duration: 9 Nov 201512 Nov 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9489
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference22nd International Conference on Neural Information Processing, ICONIP 2015
Country/TerritoryTurkey
CityIstanbul
Period9/11/1512/11/15

Keywords

  • Data association
  • Maximum a posteriori estimation
  • Online multi-object tracking
  • Sequential trajectory prior

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