Título: A model for simulating crowds based on synthetic vision and cost functions

Data: 23/01/2015 Horário: 14h Local: Sala de Seminários Bloco 952

Resumo: Most recent crowd simulation algorithms equip agents with a synthetic vision component for steering. They offer promising perspectives by more realistically imitating the way humans navigate according to what they perceive of their environment. Here, we propose a new perception/motion loop
to steer agents along collision free trajectories that significantly improves the quality of vision-based crowd simulators. In contrast with previous solutions - which make
agents avoid collisions in a purely reactive way - we suggest exploring the full range of possible adaptations and to retain the locally optimal one.

Banca:

• JOAQUIM BENTO CAVALCANTE NETO (UFC – Orientador)
• CRETO AUGUSTO VIDAL  (UFC- Coorientador)
• EMANUELE MARQUES DOS SANTOS  (UFC)