Title
Crowd Light: Evaluating the Perceived Fidelity of Illuminated Dynamic Scenes
Abstract
Rendering realistic illumination effects for complex animated scenes with many dynamic objects or characters is computationally expensive. Yet, it is not obvious how important such accurate lighting is for the overall perceived realism in these scenes. In this paper, we present a methodology to evaluate the perceived fidelity of illumination in scenes with dynamic aggregates, such as crowds, and explore several factors which may affect this perception. We focus in particular on evaluating how a popular spherical harmonics lighting method can be used to approximate realistic lighting of crowds. We conduct a series of psychophysical experiments to explore how a simple approach to approximating global illumination, using interpolation in the temporal domain, affects the perceived fidelity of dynamic scenes with high geometric, motion, and illumination complexity. We show that the complexity of the geometry and temporal properties of the crowd entities, the motion of the aggregate as a whole, the type of interpolation (i.e., of the direct and/or indirect illumination coefficients), and the presence or absence of colour all affect perceived fidelity. We show that high (i.e., above 75%) levels of perceived scene fidelity can be maintained while interpolating indirect illumination for intervals of up to 30 frames, resulting in a greater than three-fold rendering speed-up. © 2012 Wiley Periodicals, Inc.
Year
DOI
Venue
2012
10.1111/j.1467-8659.2012.03057.x
Comput. Graph. Forum
Keywords
DocType
Volume
perceived fidelity,scene fidelity,dynamic aggregate,dynamic object,indirect illumination,approximate realistic lighting,realistic illumination effect,global illumination,illumination complexity,illuminated dynamic scenes,crowd light,indirect illumination coefficient,accurate lighting,computer science
Journal
31
Issue
ISSN
Citations 
2pt4
0167-7055
9
PageRank 
References 
Authors
0.49
28
6
Name
Order
Citations
PageRank
adrian jarabo116415.17
Tom Van Eyck290.49
Veronica Sundstedt331433.61
Kavita Bala42046138.75
diego gutierrez5126391.03
Carol O'Sullivan682548.93