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Crowd behavior characterization for scene tracking

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

Résultats de recherche: Le chapitre dans un livre, un rapport, une anthologie ou une collectionContribution à une conférenceRevue par des pairs

1 Citation (Scopus)

Résumé

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.

langue originaleAnglais
titre2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019
EditeurInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronique)9781728109909
Les DOIs
étatPublié - 1 sept. 2019
Modification externeOui
Evénement16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019 - Taipei, Taiwan
Durée: 18 sept. 201921 sept. 2019

Série de publications

Nom2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019

Une conférence

Une conférence16th IEEE International Conference on Advanced Video and Signal Based Surveillance, AVSS 2019
Pays/TerritoireTaiwan
La villeTaipei
période18/09/1921/09/19

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