Name
Abstract | ||
|---|---|---|
A new definition is given to the problem of light positioning in a closed environment, aiming at obtaining, for a global illumination radiosity solution, the position and emission power for a given number of lights that provide a desired illumination at a minimum total emission power. Such a desired illumination is expressed using minimum and/or maximum values of irradiance allowed, resulting in a combinatory optimization problem. A pre-process computes and stores irradiances for a pre-established set of light positions by means of a radiosity random walk. The reuse of photon paths makes this pre-process reasonably cheap. Different heuristic search algorithms, combined to linear programming, are discussed and compared, from the simplest hill climbing strategies to the more sophisticated population-based and hybrid approaches. The paper shows how the presented approaches make it possible to obtain a good solution to the problem at a reasonable cost. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1016/j.engappai.2011.11.009 | Eng. Appl. of AI |
Keywords | Field | DocType |
light positioning,heuristic search,emission power,good solution,closed environment,global illumination radiosity solution,pre-process compute,radiosity random walk,light position,combinatory optimization problem,minimum total emission power,irradiance,particle swarm optimization,random walk,genetic algorithms,hill climbing | Hill climbing,Population,Heuristic,Mathematical optimization,Computer science,Global illumination,Artificial intelligence,Linear programming,Radiosity (computer graphics),Optimization problem,Genetic algorithm,Machine learning | Journal |
Volume | Issue | ISSN |
25 | 3 | 0952-1976 |
Citations | PageRank | References |
7 | 0.53 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Francesc Castro | 1 | 34 | 4.13 |
| Esteve del Acebo | 2 | 76 | 11.10 |
| Mateu Sbert | 3 | 1108 | 123.95 |