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Crowd behavior characterization for scene tracking

  • Université Paris-Saclay
  • LIF
  • Institut Polytechnique de Paris

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

1 Citation (Scopus)

Abstract

In this work, we perform an in-depth analysis of the specific difficulties a crowded scene dataset raises for tracking algorithms. Starting from the standard characteristics depicting the crowd and their limitations, we introduce six entropy measures related to the motion patterns and to the appearance variability of the individuals forming the crowd, and one appearance measure based on Principal Component Analysis. The proposed measures are discussed on synthetic configurations and on multiple real datasets. These criteria are able to characterize the crowd behavior at a more detailed level and may be helpful for evaluating the tracking difficulty of different datasets. The results are in agreement with the perceived difficulty of the scenes.

Original languageEnglish
Title of host publication2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728109909
DOIs
Publication statusPublished - 1 Sept 2019
Externally publishedYes
Event16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019 - Taipei, Taiwan, Province of China
Duration: 18 Sept 201921 Sept 2019

Publication series

Name2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019

Conference

Conference16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019
Country/TerritoryTaiwan, Province of China
CityTaipei
Period18/09/1921/09/19

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