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1、Copyright 2007 by the Association for Computing Machinery Inc Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for commercial advantage and that copies bear this notice and the
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3、Permissions Dept ACM Inc fax 1 212 869 0481 or e mail permissions acm org Symposium on Computer Animation 2007 San Diego CA August 03 04 2007 2007 ACM 978 1 59593 624 4 07 0008 5 00 Eurographics ACM SIGGRAPH Symposium on Computer Animation 2007 D Metaxas and J Popovic Editors Controlling Individual
4、Agents in High Density Crowd Simulation N Pelechano J M Allbeck and N I Badler University of Pennsylvania USA Abstract Simulating the motion of realistic large dense crowds of autonomous agents is still a challenge for the computer graphics community Typical approaches either resemble particle simul
5、ations where agents lack orientation controls or are conservative in the range of human motion possible agents lack psychological state and aren t allowed to push each other Our HiDAC system for High Density Autonomous Crowds focuses on the problem of simulating the local motion and global wayfindin
6、g behaviors of crowds moving in a natural manner within dynamically changing virtual environments By applying a combination of psychological and geometrical rules with a social and physical forces model HiDAC exhibits a wide variety of emergent behaviors from agent line formation to pushing behavior
7、 and its consequences relative to the current situation personalities of the individuals and perceived social density CR Categories I 3 7 Computer Graphics Three Dimensional Graphics and Realism Animation I 6 8 Simulation and Modeling Types of Simulation Animation 1 Introduction Animating motion for
8、 large crowds has been an important goal in the computer graphics movie and video games communities There has been a considerable effort on locomotion path planning navigation in large virtual environments and realistic behavior simulation using cognitive models We classify crowd agent motions by th
9、ree main approaches social forces models rule based models and cellular automata models Although much effort has gone into improving the behavioral realism of each of these approaches none of the current models can realistically animate high density crowds Social forces models tend to create simulat
10、ions that look more like particle animation than human movement Cellular automata models limit agent spatial movements and tend to expose the underlying checkerboard of cells when crowd density is high Finally rule based models either don t consider collision detection and repulsion at all or adopt
11、very conservative approaches through the use of waiting rules which work fine for low densities in everyday life simulation but lack realism for high density or panic situations Figure 1 shows a taxonomy for crowd simulation and compares our model HiDAC High Density Autonomous Crowds with the main m
12、odels in the literature along the dimensions of animation realism and crowd density HiDAC addresses the problem of simulating high density crowds of autonomous agents moving in a natural manner in dynamically changing virtual environments Our solution to the problem of realistically simulating local
13、 motion under different situations and agent personalities uses psychological physiological and geometrical rules combined with physical forces Since applying the same N Pelechano J M Allbeck but when the crowd is very dense then the right preference is not so obvious and several bi directional flow
14、s can emerge Di 1 5m Modifying the length of the collision avoidance rectangle and reducing the angle for right preference based on perceived density achieves this behavior Figure 5 shows different bi directional flow rate formation for low and high densities Figure 5b shows the result if the length
15、 of viewing rectangle and right preference parameters are not affected by density The emergent behavior shows an unrealistic triangle of people moving in opposite directions and awhile later in the simulation two perfectly formed groups of people appear to move in opposite directions which is less c
16、ommon in real high density crowds HiDAC produces an interesting emergent counterflow behavior for high density crowds Figure 5c the formation of lanes of people moving in the same direction intermingled among lanes moving in the opposite direction This is a behavior that is often observed in real crowds and it emerges here even though it is not explicitly implemented a b c Figure 5 Bi directional flows People with blonde hair walk towards the left while dark haired people walk towards the right
