The PAG Crowd: A Graph Based Approach for Efficient Data-Driven Crowd Simulation

2014 ◽  
Vol 33 (8) ◽  
pp. 95-108 ◽  
Author(s):  
P. Charalambous ◽  
Y. Chrysanthou
Keyword(s):  
Crowd Simulation ◽  
Data Driven ◽  
Efficient Data

scholarly journals Palmprint recognition with an efficient data driven ensemble classifier

2019 ◽  
Vol 126 ◽  
pp. 21-30 ◽  
Author(s):  
Imad Rida ◽  
Romain Herault ◽  
Gian Luca Marcialis ◽  
Gilles Gasso
Keyword(s):  
Ensemble Classifier ◽  
Data Driven ◽  
Palmprint Recognition ◽  
Efficient Data

Efficient data-driven evaluation: Theory and implementation

1990 ◽  
Vol 10 (4) ◽  
pp. 367-385
Author(s):  
Harrick M. Vin ◽  
Francine Berman ◽  
James S. Mattson
Keyword(s):  
Data Driven ◽  
Evaluation Theory ◽  
Efficient Data

Data-driven Crowd Modeling Techniques: A Survey

2022 ◽  
Vol 32 (1) ◽  
pp. 1-33
Author(s):  
Jinghui Zhong ◽  
Dongrui Li ◽  
Zhixing Huang ◽  
Chengyu Lu ◽  
Wentong Cai
Keyword(s):  
Game Design ◽  
State Of The Art ◽  
Crowd Simulation ◽  
Data Driven ◽  
Future Research ◽  
Crowd Modeling ◽  
The Past ◽  
Modeling Techniques ◽  
Comprehensive Survey ◽  
Data Driven Modeling

Data-driven crowd modeling has now become a popular and effective approach for generating realistic crowd simulation and has been applied to a range of applications, such as anomaly detection and game design. In the past decades, a number of data-driven crowd modeling techniques have been proposed, providing many options for people to generate virtual crowd simulation. This article provides a comprehensive survey of these state-of-the-art data-driven modeling techniques. We first describe the commonly used datasets for crowd modeling. Then, we categorize and discuss the state-of-the-art data-driven crowd modeling methods. After that, data-driven crowd model validation techniques are discussed. Finally, six promising future research topics of data-driven crowd modeling are discussed.

Sign in / Sign up

Export Citation Format

Share Document