“Morphable crowds”
Conference:
Type(s):
Title:
- Morphable crowds
Session/Category Title: Curves, characters & crowds
Presenter(s)/Author(s):
Moderator(s):
Abstract:
Crowd simulation has been an important research field due to its diverse range of applications that include film production, military simulation, and urban planning. A challenging problem is to provide simple yet effective control over captured and simulated crowds to synthesize intended group motions. We present a new method that blends existing crowd data to generate a new crowd animation. The new animation can include an arbitrary number of agents, extends for an arbitrary duration, and yields a natural-looking mixture of the input crowd data. The main benefit of this approach is to create new spatio-temporal crowd behavior in an intuitive and predictable manner. It is accomplished by introducing a morphable crowd model that allows us to encode the formations and individual trajectories in crowd data. Then, its original spatio-temporal behavior can be reconstructed and interpolated at an arbitrary scale using our morphable model.
References:
1. Ali, S., and Shah, M. 2008. Floor fields for tracking in high density crowd scenes. In ECCV ’08: Proceedings of the 10th European Conference on Computer Vision, 1–14. Google ScholarDigital Library
2. Andriluka, M., Roth, S., and Schiele, B. 2008. People-tracking-by-detection and people-detection-by-tracking. In Proc. IEEE Conference on Computer Vision and Pattern Recognition, 2008. (CVPR 2008), 1–8.Google ScholarCross Ref
3. Courty, N., and Corpetti, T. 2007. Crowd motion capture. Computer Animation and Virtual Worlds 18, 4–5, 361–370. Google ScholarDigital Library
4. Gibbons, A. 1985. Algorithmic Graph Theory. Cambridge University Press.Google Scholar
5. Guy, S. J., Chhugani, J., Kim, C., Satish, N., Dubey, P., Lin, M., and Manocha, D. 2009. Clearpath: Highly parallel collision avoidance for multi-agent simulations. In SCA ’09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics symposium on Computer animation, 177–187. Google ScholarDigital Library
6. Kamphuis, A., and Overmars, M. H. 2004. Finding paths for coherent groups using clearance. In SCA ’04: Proceedings of the 2004 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 233–242. Google ScholarDigital Library
7. Kim, M., Hyun, K. L., Kim, J., and Lee, J. 2009. Synchronized multi-character motion editing. ACM Transactions on Graphics (SIGGRAPH 2009) 28, 3, 1–9. Google ScholarDigital Library
8. Kovar, L., and Gleicher, M. 2004. Automated extraction and parameterization of motions in large data sets. ACM Transactions on Graphics (SIGGRAPH 2004) 23, 3, 559–568. Google ScholarDigital Library
9. Kwon, T., Lee, K. H., Lee, J., and Takahashi, S. 2008. Group motion editing. ACM Transactions on Graphics (SIGGRAPH 2008) 27, 3, 1–8. Google ScholarDigital Library
10. Lai, Y.-C., Chenney, S., and Fan, S. 2005. Group motion graphs. In SCA ’05: Proceedings of the 2005 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 281–290. Google ScholarDigital Library
11. Lee, J., Chai, J., Reitsma, P. S. A., Hodgins, J. K., and Pollard, N. S. 2002. Interactive control of avatars animated with human motion data. ACM Transactions on Graphics (SIGGRAPH 2002) 21, 3, 491–500. Google ScholarDigital Library


