Journal paper in MDPI Computers
Our journal article “Virtual Forestry Generation: Evaluating Models for Tree Placement in Games” has been accepted for publication in MDPI Computers, in a special issue with invited extended publications from EG CGVC 2019.
In this article, we present a user study into virtual forests, using three different approaches of spatially distributing trees to approximate a plant community. These three approaches consisted of a random uniform distribution algorithm, a asymmetric plant competition model, and an iterative random distribution algorithm for creating clusters of trees. Our results demonstrate that the asymmetric plant competition model (the ‘Propagation’ algorithm) produces forests which were rated the highest in terms of playability and believability, for both 2D and 3D aerial perspectives.
B. Williams, P. D. Ritsos, and C. Headleand, “Virtual Forestry Generation: Evaluating Models for Tree Placement in Games,” Computers, vol. 9, no. 1, Mar. 2020.
A handful of approaches have been previously proposed to generate procedurally virtual forestry for virtual worlds and computer games, including plant growthmodels and point distribution methods. However, there has been no evaluation to date which assesses how effective these algorithms are at modelling real-world phenomena. In this paper we tackle this issue by evaluating three algorithms used in the generation of virtual forests – a randomly uniform point distribution method (control), a plant competition model, and an iterative random point distribution technique.Our results show that a plant competition model generated more believable content when viewed from an aerial perspective. Interestingly however, we also found that a randomly uniform point distribution method produced forestry which was rated higher in playability and photorealism, when viewed from a first-person perspective. We conclude that the objective of the game designer is important to consider when selecting an algorithm to generate forestry, as the algorithms produce forestry which is perceived differently.