http://de.evo-art.org/index.php?action=history&feed=atom&title=Virtual_Photography_Using_Multi-Objective_Particle_Swarm_Optimization 2026-05-18T04:25:06Z Versionsgeschichte dieser Seite in de_evolutionary_art_org MediaWiki 1.27.4 http://de.evo-art.org/index.php?title=Virtual_Photography_Using_Multi-Objective_Particle_Swarm_Optimization&diff=3268&oldid=prev 2015-01-13T19:38:39Z

<p>Die Seite wurde neu angelegt: „== Reference == W. Barry and <a href="/index.php?title=Brian_J._Ross" title="Brian J. Ross">Brian J. Ross</a>: <a href="/index.php?title=Virtual_Photography_Using_Multi-Objective_Particle_Swarm_Optimization" title="Virtual Photography Using Multi-Objective Particle Swarm Optimization">Virtual Photography Using Multi-Objective Particle Swarm Optimization</a>. GECCO 2014, pp. 285-292, Vancouver, …“</p> <p><b>Neue Seite</b></p><div>== Reference ==<br /> W. Barry and [[Brian J. Ross]]: [[Virtual Photography Using Multi-Objective Particle Swarm Optimization]]. GECCO 2014, pp. 285-292, Vancouver, BC, July 2014. <br /> <br /> == DOI ==<br /> http://dx.doi.org/10.1145/2576768.2598210 <br /> <br /> == Abstract ==<br /> Particle swarm optimization (PSO) is a stochastic population-based search algorithm that is inspired by the flocking behaviour of birds. Here, a PSO is used to implement swarms of cameras flying through a virtual world in search of an image that satisfies a set of compositional objectives, for example, the rule of thirds and horizon line rules. To effectively process these multiple, and possible conflicting, criteria, a new multi-objective PSO algorithm called the sum of ranks PSO (SR-PSO) is introduced. The SR-PSO is useful for solving high-dimensional search problems, while discouraging degenerate solutions that can arise with other approaches. Less user intervention is required for the SR-PSO, as compared to a conventional PSO. A number of problems using different virtual worlds and user-supplied objectives were studied. In all cases, solution images were obtained that satisfied the majority of given objectives. The SR-PSO is shown to be superior to other algorithms in solving the high-dimensional virtual photography problems studied.<br /> <br /> == Extended Abstract ==<br /> <br /> == Bibtex == <br /> <br /> == Used References ==<br /> Rafid Abdullah , Marc Christie , Guy Schofield , Christophe Lino , Patrick Olivier, Advanced composition in virtual camera control, Proceedings of the 11th international conference on Smart graphics, July 18-20, 2011, Bremen, Germany http://dl.acm.org/citation.cfm?id=2032570&amp;CFID=588525319&amp;CFTOKEN=29804931<br /> <br /> Autodesk. 3ds max 2009. http://usa.autodesk.com/, August 2012.<br /> <br /> William Bares , Byungwoo Kim, Generating virtual camera compositions, Proceedings of the 6th international conference on Intelligent user interfaces, p.9-12, January 14-17, 2001, Santa Fe, New Mexico, USA http://doi.acm.org/10.1145/359784.359824<br /> <br /> W. Barry. 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IEEE Trans. on Multimedia, 15, June 2013. <br /> <br /> <br /> == Links ==<br /> === Full Text === <br /> http://www.cosc.brocku.ca/~bross/psoPhotos/GECCO_2014_07_12.pptx Presentation<br /> <br /> [[intern file]]<br /> <br /> === Sonstige Links ===</div>

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