TY - GEN
T1 - Diversified virtual camera composition
AU - Preuss, Mike
AU - Burelli, Paolo
AU - Yannakakis, Georgios N.
PY - 2012
Y1 - 2012
N2 - The expressive use of virtual cameras and the automatic generation of cinematics within 3D environments shows potential to extend the communicative power of films into games and virtual worlds. In this paper we present a novel solution to the problem of virtual camera composition based on niching and restart evolutionary algorithms that addresses the problem of diversity in shot generation by simultaneously identifying multiple valid camera camera configurations. We asses the performance of the proposed solution against a set of state-of-the-art algorithms in virtual camera optimisation.
AB - The expressive use of virtual cameras and the automatic generation of cinematics within 3D environments shows potential to extend the communicative power of films into games and virtual worlds. In this paper we present a novel solution to the problem of virtual camera composition based on niching and restart evolutionary algorithms that addresses the problem of diversity in shot generation by simultaneously identifying multiple valid camera camera configurations. We asses the performance of the proposed solution against a set of state-of-the-art algorithms in virtual camera optimisation.
KW - Virtual Camera Composition
KW - Evolutionary Algorithms
KW - Cinematic Generation
KW - 3D Environments
KW - Shot Diversity Optimization
KW - Virtual Camera Composition
KW - Evolutionary Algorithms
KW - Cinematic Generation
KW - 3D Environments
KW - Shot Diversity Optimization
U2 - 10.1007/978-3-642-29178-4_27
DO - 10.1007/978-3-642-29178-4_27
M3 - Conference article
SN - 0001-0782
SP - 265
EP - 274
JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -