Multi-modal Computer Vision for the Detection of Multi-scale Crowd Physical Motions and Behavior in Confined Spaces
- 18 December 2015
- book chapter
- Published by Springer Nature
- p. 162-173
Abstract
No abstract availableKeywords
This publication has 18 references indexed in Scilit:
- Context Ontology Modelling for Improving Situation Awareness and Crowd Evacuation from Confined Spaces2015
- Vision-Based Analysis of Small Groups in Pedestrian CrowdsIEEE Transactions on Pattern Analysis and Machine Intelligence, 2012
- Efficient tracking using a robust motion estimation techniqueMultimedia Tools and Applications, 2012
- Group Level Activity Recognition in Crowded Environments across Multiple Cameras2010
- You'll never walk alone: Modeling social behavior for multi-target tracking2009
- FIRST-ORDER MACROSCOPIC MODELLING OF HUMAN CROWD DYNAMICSMathematical Models and Methods in Applied Sciences, 2008
- Friction effects and clogging in a cellular automaton model for pedestrian dynamicsPhysical Review E, 2003
- Simulation of pedestrian dynamics using a two-dimensional cellular automatonPhysica A: Statistical Mechanics and its Applications, 2001
- Automatic estimation of crowd density using textureSafety Science, 1998
- Social force model for pedestrian dynamicsPhysical Review E, 1995