Self-Organizing maps for the automatic interpretation of crowd dynamics

Monekosso, N.; Zhan, Beibei; Remagnino, Paolo; Monekosso, Dorothy; Velastin, Sergio

Abstract

This paper introduces the use of self-organizing maps for the visualization of crowd dynamics and to learn models of the dominant motions of crowds in complex scenes. The self-organizing map (SOM) model is a well known dimensionality reduction method proved to bear resemblance with characteristics of the human brain, representing sensory input by topologically ordered computational maps. This paper proposes algorithms to learn and compare crowd dynamics with the SOM model. Different information is employed as input to the used SOM. Qualitative and quantitative results are presented in the paper. © Springer-Verlag Berlin Heidelberg 2008.

• Presentation Conference Type: Conference Paper (published)
• Conference Name: The 4th International Symposium on Advances in Visual Computing
• Publication Date: Dec 1, 2008
• Journal: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
• Print ISSN: 0302-9743
• Publisher: Springer Verlag
• Peer Reviewed: Not Peer Reviewed
• Volume: 5358 LNCS
• Issue: PART 1
• Pages: 440-449
• DOI: https://doi.org/10.1007/978-3-540-89639-5_42
• Keywords: self-organizing maps, crowd dynamics
• Public URL: https://uwe-repository.worktribe.com/output/1022857
• Additional Information: Additional Information : id: 1; issn: print 0302-9743; issn: electronic 1611-3349; isbn: print 978-3-540-89638-8; isbn: electronic 978-3-540-89639-5; Title of Conference or Conference Proceedings : The 4th International Symposium on Advances in Visual Computing