Augmentation of virtual agents in real crowd videos

Date
2019
Advisor
Instructor
Source Title
Signal, Image and Video Processing
Print ISSN
1863-1711
Electronic ISSN
Publisher
Springer
Volume
13
Issue
Pages
643 - 650
Language
English
Type
Article
Journal Title
Journal ISSN
Volume Title
Abstract

Augmenting virtual agents in real crowd videos is an important task for different applications from simulations of social environments to modeling abnormalities in crowd behavior. We propose a framework for this task, namely for augmenting virtual agents in real crowd videos. We utilize pedestrian detection and tracking algorithms to automatically locate the pedestrians in video frames and project them into our simulated environment, where the navigable area of the simulated environment is available as a navigation mesh. We represent the real pedestrians in the video as simple three-dimensional (3D) models in our simulation environment. 3D models representing real agents and the augmented virtual agents are simulated using local path planning coupled with a collision avoidance algorithm. The virtual agents augmented into the real video move plausibly without colliding with static and dynamic obstacles, including other virtual agents and the real pedestrians.

Course
Other identifiers
Book Title
Keywords
Data-driven simulation, Pedestrian detection, Pedestrian tracking, Crowd simulation, Collision avoidance, Augmented reality
Citation
Published Version (Please cite this version)