Gradient-based steering for vision-based crowd simulation algorithms

Gradient-based steering for vision-based crowd simulation algorithms

Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives through a more realistic simulation of the way humans navigate according to their perception of the surrounding environment. In this paper, we propose a new perception/motion loop to steering agents along collision free trajectories that significantly improves t...

Additional Material Gradient-based steering for vision-based crowd simulation algorithms

Simulation of Crowd Problems for Computer Vision

This work presents an approach for generating video evidence of dangerous situations in crowded scenes. The scenarios of interest are those with high safety risk such as blocked exit, collapse of a person in the crowd, and escape panic. Real visual evidence for these scenarios is rare or unsafe to reproduce in a controllable way. Thus there is a need for simulation to allow training and validat...

Cognitive Emotional Based Architecture for Crowd Simulation

This paper presents a new approach to model crowd behaviour in normal and risky situations. Our model is based on human cognitive characteristics specially personality type, perception and emotion that we assume relevant to individuals’ behavioural decisions. The model supports an efficient interaction between the different architecture components to provide behaviour. A formal definition of co...

Velocity-based models for crowd simulation

Velocity-based models belong to the category of microscopic crowd simulation models. They recently appeared in the crowd simulation literature. They mathematically formulate microscopic interactions as a function of agents' states and their derivatives. In the case of collision avoidance, this property provides agents with the ability to produce anticipated smooth reactions, with great impact o...