Crowd Behavior Characterization for Scene Tracking

Séverine Dubuisson 1 Isabelle Bloch 2 Gianni Franchi 3 Emanuel Aldea 4
1 LIS - Laboratoire d'Informatique et Systèmes
2 Télécom ParisTech
3 CMM - Centre de Morphologie Mathématique
4 UP11 - Université Paris-Sud - Paris 11
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 en-tropy 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.
Document type :
Conference papers
Complete list of metadatas

Cited literature [14 references]  Display  Hide  Download
https://hal.archives-ouvertes.fr/hal-02472760
Contributor : Emanuel Aldea <>
Submitted on : Monday, February 10, 2020 - 1:08:56 PM
Last modification on : Sunday, February 16, 2020 - 1:24:32 AM

File

FranchiAVSS19.pdf
Files produced by the author(s)

Identifiers

Collections

ENSMP_CMM | ENSMP | PARISTECH | PSL | IP_PARIS | CNRS | INSTITUT-TELECOM | UNIV-PARIS-SACLAY | LIS-LAB | UNIV-TLN | UNIV-AMU

Citation

Séverine Dubuisson, Isabelle Bloch, Gianni Franchi, Emanuel Aldea. Crowd Behavior Characterization for Scene Tracking. 2019 16th IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS), Sep 2019, Taipei, Taiwan. pp.1-8, ⟨10.1109/AVSS.2019.8909893⟩. ⟨hal-02472760⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

9

Files downloads

11

Contact

Informations

CCSD