Perception of Complex Aggregates

Ganesh Ramanarayanan, Kavita Bala and James Ferwerda

Proceedings of SIGGRAPH 2008 (SIGGRAPH 2008, ACM Transactions on Graphics, Volume 27, Number 3)




Abstract: Aggregates of individual objects, such as forests, crowds, and piles of fruit, are a common source of complexity in computer graphics scenes. When viewing an aggregate, observers attend less to individual objects and focus more on overall properties such as numerosity, variety, and arrangement. Paradoxically, rendering and modeling costs increase with aggregate complexity, exactly when observers are attending less to individual objects.
In this paper we take some first steps to characterize the limits of visual coding of aggregates to efficiently represent their appearance in scenes. We describe psychophysical experiments that explore the roles played by the geometric and material properties of individual objects in observersí abilities to discriminate different aggregate collections. Based on these experiments we derive metrics to predict when two aggregates have the same appearance, even when composed of different objects. In a follow-up experiment we confirm that these metrics can be used to predict the appearance of a range of realistic aggregates. Finally, as a proof-of-concept we show how these new aggregate perception metrics can be applied to simplify scenes by allowing substitution of geometrically simpler aggregates for more complex ones without changing appearance.

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Acknowledgments: National Science Foundation (NSF), Intel Corporation.