SteerBug: an interactive framework for specifying and detecting steering behaviors Export

@inproceedings{citeulike:5743685, abstract = {The size of crowds that modern computer games and urban simulations are capable of handling has given rise to the challenging problem of debugging and testing massive simulations of autonomous agents. In this paper, we propose SteerBug: an interactive framework for specifying and detecting steering behaviors. Our framework computes a set of time-varying metrics for agents and their environment, which characterize steering behaviors. We identify behaviors of interest by applying conditions (rules) or user defined sketches on the associated metrics. The behaviors we can specify and detect include unnatural steering, plainly incorrect results, or application-specific behaviors of interest. Our framework is extensible and independent of the specifics of any steering approach. To our knowledge, this is the first work that aims to provide a computational framework for specifying and detecting crowd behaviors in animation.}, address = {New York, NY, USA}, author = {Kapadia, Mubbasir and Singh, Shawn and Allen, Brian and Reinman, Glenn and Faloutsos, Petros}, booktitle = {SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation}, citeulike-article-id = {5743685}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1599470.1599497}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1599470.1599497}, doi = {10.1145/1599470.1599497}, isbn = {978-1-60558-610-6}, keywords = {crowd, group, steering}, location = {New Orleans, Louisiana}, pages = {209--216}, posted-at = {2009-09-08 19:21:32}, priority = {2}, publisher = {ACM}, title = {SteerBug: an interactive framework for specifying and detecting steering behaviors}, url = {http://dx.doi.org/10.1145/1599470.1599497}, year = {2009} }

TY - CONF ID - citeulike:5743685 L3 - citeulike-article-id:5743685 N2 - The size of crowds that modern computer games and urban simulations are capable of handling has given rise to the challenging problem of debugging and testing massive simulations of autonomous agents. In this paper, we propose SteerBug: an interactive framework for specifying and detecting steering behaviors. Our framework computes a set of time-varying metrics for agents and their environment, which characterize steering behaviors. We identify behaviors of interest by applying conditions (rules) or user defined sketches on the associated metrics. The behaviors we can specify and detect include unnatural steering, plainly incorrect results, or application-specific behaviors of interest. Our framework is extensible and independent of the specifics of any steering approach. To our knowledge, this is the first work that aims to provide a computational framework for specifying and detecting crowd behaviors in animation. CY - New Orleans, Louisiana SN - 978-1-60558-610-6 AD - New York, NY, USA EP - 216 TI - SteerBug: an interactive framework for specifying and detecting steering behaviors PB - ACM T2 - SCA '09: Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation SP - 209 KW - crowd KW - group KW - steering AU - Kapadia, Mubbasir AU - Singh, Shawn AU - Allen, Brian AU - Reinman, Glenn AU - Faloutsos, Petros PY - 2009/// UR - http://dx.doi.org/10.1145/1599470.1599497 ER -