Diversified virtual camera composition

Mike Preuss; Paolo Burelli; Georgios N. Yannakakis

doi:10.1007/978-3-642-29178-4_27

Diversified virtual camera composition

Mike Preuss
, Paolo Burelli
, Georgios N. Yannakakis

Research output: Journal Article or Conference Article in Journal › Conference article › Research › peer-review

Abstract

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.

Original language	English
Conference proceedings	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages (from-to)	265-274
Number of pages	10
ISSN	0001-0782
DOIs	https://doi.org/10.1007/978-3-642-29178-4_27
Publication status	Published - 2012

Keywords

Virtual Camera Composition
Evolutionary Algorithms
Cinematic Generation
3D Environments
Shot Diversity Optimization

Access to Document

10.1007/978-3-642-29178-4_27

http://www.mendeley.com/research/diversified-virtual-camera-composition

Cite this

@inproceedings{b20ac6328c0b47688713417b80c0d406,

title = "Diversified virtual camera composition",

abstract = "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.",

keywords = "Virtual Camera Composition, Evolutionary Algorithms, Cinematic Generation, 3D Environments, Shot Diversity Optimization, Virtual Camera Composition, Evolutionary Algorithms, Cinematic Generation, 3D Environments, Shot Diversity Optimization",

author = "Mike Preuss and Paolo Burelli and Yannakakis, \{Georgios N.\}",

year = "2012",

doi = "10.1007/978-3-642-29178-4\_27",

language = "English",

pages = "265--274",

journal = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

issn = "0001-0782",

publisher = "Association for Computing Machinery",

}

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 -

Diversified virtual camera composition

Abstract

Keywords

Access to Document

Fingerprint

Cite this