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Title: Real-time rendering of animated crowd scenes
Author: Lister, Wayne Daniel
ISNI:       0000 0004 2717 959X
Awarding Body: University of East Anglia
Current Institution: University of East Anglia
Date of Award: 2011
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Simulated crowds can be found in a wide range of real-time applications. Examples include urban planning and cultural heritage visualizations, disaster and military training simulations, through to perhaps most prominently the use of virtual crowds purely for entertainment purposes in the gaming industry. Crowd simulation is very much an interdisciplinary concern and its importance has motivated researchers from a variety of fields; including computer graphics, psychology and robotics. This thesis considers the problem purely from a computer graphics perspective and introduces three new techniques to animate and draw a crowd of virtual humans in real-time. Contribution 1 addresses vertex skinning and begins by noting that for scenes in which many thousands of characters are visualized, it is often the case that individuals are doing much the same thing. A caching system is therefore proposed and used to accelerate the rendering of a crowd by taking advantage of the temporal and intra-crowd coherencies that are inherent within a populated scene. The approach can be considered a geometric interpretation of dynamic impostors and is best suited to low-entropy scenes such as sports fans clapping and cheering in a stadium. Contributions 2 and 3 consider skeletal animation. For performance reasons previous works have relied heavily on pre-computation when animating their crowds but the associated trade- off is control. It is currently far too difficult to make members of a crowd do anything other than play a scripted animation clip and high-level techniques such as inverse kinematics are yet to be fully explored. This thesis describes how a combination of compute shaders and middleware can remove the need for pre-computation and enable a huge library of 'off-the- shelf' animation techniques, not usually available when visualizing a crowd, to be deployed on thousands of crowd members simultaneously.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available