New Algorithms for Computing Field of Vision over 2D Grids

TL;DR

This paper introduces new algorithms for computing the field of vision in 2D grids that significantly improve efficiency at high resolutions, enabling more detailed FOV-based video game design.

Contribution

The paper presents novel algorithms utilizing spatial data structures and incremental updates to enhance FOV computation speed over existing methods.

Findings

Substantial reduction in computation time at large grid sizes

Effective use of spatial data structures for FOV calculation

Enabling high-resolution FOV-based game design

Abstract

The aim of this paper is to propose new algorithms for Field of Vision (FOV) computation which improve on existing work at high resolutions. FOV refers to the set of locations that are visible from a specific position in a scene of a computer game. We summarize existing algorithms for FOV computation, describe their limitations, and present new algorithms which aim to address these limitations. We first present an algorithm which makes use of spatial data structures in a way which is new for FOV calculation. We then present a novel technique which updates a previously calculated FOV, rather than re-calculating an FOV from scratch. We compare our algorithms to existing FOV algorithms and show they provide substantial improvements to running time. Our algorithms provide the largest improvement over existing FOV algorithms at large grid sizes, thus allowing the possibility of the design of high resolution FOV-based video games.