Document Type

Journal Article

Publication Title

IEEE Access

Volume

8

First Page

216491

Last Page

216506

Publisher

IEEE

School

School of Science

RAS ID

32512

Funders

Edith Cowan University - Open Access Support Scheme 2020

Comments

Pech, A., Lam, C. P., & Masek, M. (2020). Quantifiable isovist and graph-based measures for automatic evaluation of different area types in virtual terrain generation. IEEE Access, 8, 216491-216506. https://doi.org/10.1109/ACCESS.2020.3041276

Abstract

© 2013 IEEE. This article describes a set of proposed measures for characterizing areas within a virtual terrain in terms of their attributes and their relationships with other areas for incorporating game designers' intent in gameplay requirement-based terrain generation. Examples of such gameplay elements include vantage point, strongholds, chokepoints and hidden areas. Our measures are constructed on characteristics of an isovist, that is, the volume of visible space at a local area and the connectivity of areas within the terrain. The calculation of these measures is detailed, in particular we introduce two new ways to accurately and efficiently calculate the 3D isovist volume. Unlike previous research that has mainly focused on aesthetic-based terrain generation, the proposed measures address a gap in gameplay requirement-based terrain generation-the need for a flexible mechanism to automatically parameterise specified areas and their associated relationships, capturing semantic knowledge relating to high level user intent associated with specific gameplay elements within the virtual terrain. We demonstrate applications of using the measures in an evolutionary process to automatically generate terrains that include specific gameplay elements as defined by a game designer. This is significant as this shows that the measures can characterize different gameplay elements and allow gameplay elements consistent with the designers' intents to be generated and positioned in a virtual terrain without the need to specify low-level details at a model or logic level, hence leading to higher productivity and lower cost.

DOI

10.1109/ACCESS.2020.3041276

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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