Performance of optical flow techniques
International Journal of Computer Vision
Recursive non-linear estimation of discontinuous flow fields
ECCV '94 Proceedings of the third European conference on Computer vision (vol. 1)
Computation and analysis of image motion: a synopsis of current problems and methods
International Journal of Computer Vision
Dense Estimation of Fluid Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
Turning to the masters: motion capturing cartoons
Proceedings of the 29th annual conference on Computer graphics and interactive techniques
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
Hierarchical Model for Real Time Simulation of Virtual Human Crowds
IEEE Transactions on Visualization and Computer Graphics
Modeling Individual Behaviors in Crowd Simulation
CASA '03 Proceedings of the 16th International Conference on Computer Animation and Social Agents (CASA 2003)
Vision-based control of 3D facial animation
Proceedings of the 2003 ACM SIGGRAPH/Eurographics symposium on Computer animation
Flow-based video synthesis and editing
ACM SIGGRAPH 2004 Papers
SCA '04 Proceedings of the 2004 ACM SIGGRAPH/Eurographics symposium on Computer animation
Proceedings of the 2005 ACM SIGGRAPH/Eurographics symposium on Computer animation
ACM SIGGRAPH 2006 Papers
Modelling Crowd Scenes for Event Detection
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Simulation of large crowds in emergency situations including gaseous phenomena
CGI '05 Proceedings of the Computer Graphics International 2005
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
Context-sensitive data-driven crowd simulation
Proceedings of the 12th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
| Hi-index | 0.00 |
In this paper we propose an original method to animate a crowd of virtual beings in a virtual environment. Instead of relying on models to describe the motions of people along time, we suggest to use a priori knowledge on the dynamic of the crowd acquired from videos of real crowd situations. In our method this information is expressed as a time-varying motion field which accounts for a continuous flow of people along time. This motion descriptor is obtained through optical flow estimation with a specific second order regularization. Obtained motion fields are then used in a classical fixed step size integration scheme that allows to animate a virtual crowd in real-time. The power of our technique is demonstrated through various examples and possible follow-ups to this work are also described.