ITU

Interactive Virtual Cinematography

Research output: Book / Anthology / Report / Ph.D. thesisPh.D. thesisResearch

Standard

Interactive Virtual Cinematography. / Burelli, Paolo.

IT-Universitetet i København, 2012. 146 p. (ITU-DS; No. 82).

Research output: Book / Anthology / Report / Ph.D. thesisPh.D. thesisResearch

Harvard

Burelli, P 2012, Interactive Virtual Cinematography. ITU-DS, no. 82, IT-Universitetet i København.

APA

Burelli, P. (2012). Interactive Virtual Cinematography. IT-Universitetet i København. ITU-DS, No. 82

Vancouver

Burelli P. Interactive Virtual Cinematography. IT-Universitetet i København, 2012. 146 p. (ITU-DS; No. 82).

Author

Burelli, Paolo. / Interactive Virtual Cinematography. IT-Universitetet i København, 2012. 146 p. (ITU-DS; No. 82).

Bibtex

@phdthesis{bd2b620772be495e82ad24cde84f37b0,
title = "Interactive Virtual Cinematography",
abstract = "A virtual camera represents the point-of-view of the player through which sheperceives the game world and gets feedback on her actions. Thus, the virtualcamera plays a vital role in 3D computer games and aects player experienceand enjoyability in games. Interactive virtual cinematography is the process ofvisualising the content of a virtual environment by positioning and animatingthe virtual camera in the context of interactive applications such as a computergame.Camera placement and animation in games are usually directly controlled bythe player or statically predened by designers. Direct control of the camera bythe player increases the complexity of the interaction and reduces the designer'scontrol on game storytelling. A completely designer-driven camera releases theplayer from the burden of controlling the point of view, but might generateundesired camera behaviours. Furthermore, if the content of the game is procedurallygenerated, the designer might not have the necessary information todene a priori the camera positions and movements.Automatic camera control aims to dene an abstraction layer that permits tocontrol the camera using high-level and environment-independent rules. Thecamera controller should dynamically and eciently translate these rules intocamera positions and movements before (or while) the player plays the game.Automatically controlling the camera in virtual 3D dynamic environments is anopen research problem and a challenging task. From an optimisation perspectiveit is a relatively low dimensional problem (i.e. it has a minimum of 5 dimensions)but the complexity of the objective function evaluation combined with thestrict time constraints make the problem computationally complex. Moreover,the multi-objective nature of the typical camera objective function, introducesproblems such as constraints conflicts, over-constraining or under-constraining.An hypothetical optimal automatic camera control system should provide theright tool to allow designers to place cameras eectively in dynamic and unpredictableenvironments. However, there is still a limit in this approach: to bridge the gap between automatic and manual cameras the camera objective shouldbe influenced by the player. In our view, the camera control system should beable to learn camera preferences from the user and adapt the camera setting toimprove the player experience. Therefore, we propose a new approach to automaticcamera control that indirectly includes the player in the camera controlloop.To achieve this goal we have analysed the automatic camera control problemfrom a numerical optimization perspective and we have introduced a new optimization algorithm and camera control architecture able to generate real-time,smooth and well composed camera animations. Moreover, we have designedand tested an approach to model the player's camera preferences using machinelearning techniques and to tailor the automatic camera behaviour to the playerand her game-play style.Experiments show that, the novel optimisation algorithm introduced successfullyhandles highly dynamic and multi-modal tness functions such as the onestypically involved in dynamic camera control. Moreover, when applied in acommercial-standard game, the proposed automatic camera control architectureshows to be able to accurately and smoothly control the camera. Finally,the results of a user survey, conducted to evaluate the suggested methodology forcamera behaviour modelling and adaptation, shows that the resulting adaptivecinematographic experience is largely favoured by the players and it generatesa positive impact on the game performance.",
author = "Paolo Burelli",
year = "2012",
language = "English",
isbn = "978-87-7949-273-8",
publisher = "IT-Universitetet i K{\o}benhavn",
address = "Denmark",

}

RIS

TY - BOOK

T1 - Interactive Virtual Cinematography

AU - Burelli, Paolo

PY - 2012

Y1 - 2012

N2 - A virtual camera represents the point-of-view of the player through which sheperceives the game world and gets feedback on her actions. Thus, the virtualcamera plays a vital role in 3D computer games and aects player experienceand enjoyability in games. Interactive virtual cinematography is the process ofvisualising the content of a virtual environment by positioning and animatingthe virtual camera in the context of interactive applications such as a computergame.Camera placement and animation in games are usually directly controlled bythe player or statically predened by designers. Direct control of the camera bythe player increases the complexity of the interaction and reduces the designer'scontrol on game storytelling. A completely designer-driven camera releases theplayer from the burden of controlling the point of view, but might generateundesired camera behaviours. Furthermore, if the content of the game is procedurallygenerated, the designer might not have the necessary information todene a priori the camera positions and movements.Automatic camera control aims to dene an abstraction layer that permits tocontrol the camera using high-level and environment-independent rules. Thecamera controller should dynamically and eciently translate these rules intocamera positions and movements before (or while) the player plays the game.Automatically controlling the camera in virtual 3D dynamic environments is anopen research problem and a challenging task. From an optimisation perspectiveit is a relatively low dimensional problem (i.e. it has a minimum of 5 dimensions)but the complexity of the objective function evaluation combined with thestrict time constraints make the problem computationally complex. Moreover,the multi-objective nature of the typical camera objective function, introducesproblems such as constraints conflicts, over-constraining or under-constraining.An hypothetical optimal automatic camera control system should provide theright tool to allow designers to place cameras eectively in dynamic and unpredictableenvironments. However, there is still a limit in this approach: to bridge the gap between automatic and manual cameras the camera objective shouldbe influenced by the player. In our view, the camera control system should beable to learn camera preferences from the user and adapt the camera setting toimprove the player experience. Therefore, we propose a new approach to automaticcamera control that indirectly includes the player in the camera controlloop.To achieve this goal we have analysed the automatic camera control problemfrom a numerical optimization perspective and we have introduced a new optimization algorithm and camera control architecture able to generate real-time,smooth and well composed camera animations. Moreover, we have designedand tested an approach to model the player's camera preferences using machinelearning techniques and to tailor the automatic camera behaviour to the playerand her game-play style.Experiments show that, the novel optimisation algorithm introduced successfullyhandles highly dynamic and multi-modal tness functions such as the onestypically involved in dynamic camera control. Moreover, when applied in acommercial-standard game, the proposed automatic camera control architectureshows to be able to accurately and smoothly control the camera. Finally,the results of a user survey, conducted to evaluate the suggested methodology forcamera behaviour modelling and adaptation, shows that the resulting adaptivecinematographic experience is largely favoured by the players and it generatesa positive impact on the game performance.

AB - A virtual camera represents the point-of-view of the player through which sheperceives the game world and gets feedback on her actions. Thus, the virtualcamera plays a vital role in 3D computer games and aects player experienceand enjoyability in games. Interactive virtual cinematography is the process ofvisualising the content of a virtual environment by positioning and animatingthe virtual camera in the context of interactive applications such as a computergame.Camera placement and animation in games are usually directly controlled bythe player or statically predened by designers. Direct control of the camera bythe player increases the complexity of the interaction and reduces the designer'scontrol on game storytelling. A completely designer-driven camera releases theplayer from the burden of controlling the point of view, but might generateundesired camera behaviours. Furthermore, if the content of the game is procedurallygenerated, the designer might not have the necessary information todene a priori the camera positions and movements.Automatic camera control aims to dene an abstraction layer that permits tocontrol the camera using high-level and environment-independent rules. Thecamera controller should dynamically and eciently translate these rules intocamera positions and movements before (or while) the player plays the game.Automatically controlling the camera in virtual 3D dynamic environments is anopen research problem and a challenging task. From an optimisation perspectiveit is a relatively low dimensional problem (i.e. it has a minimum of 5 dimensions)but the complexity of the objective function evaluation combined with thestrict time constraints make the problem computationally complex. Moreover,the multi-objective nature of the typical camera objective function, introducesproblems such as constraints conflicts, over-constraining or under-constraining.An hypothetical optimal automatic camera control system should provide theright tool to allow designers to place cameras eectively in dynamic and unpredictableenvironments. However, there is still a limit in this approach: to bridge the gap between automatic and manual cameras the camera objective shouldbe influenced by the player. In our view, the camera control system should beable to learn camera preferences from the user and adapt the camera setting toimprove the player experience. Therefore, we propose a new approach to automaticcamera control that indirectly includes the player in the camera controlloop.To achieve this goal we have analysed the automatic camera control problemfrom a numerical optimization perspective and we have introduced a new optimization algorithm and camera control architecture able to generate real-time,smooth and well composed camera animations. Moreover, we have designedand tested an approach to model the player's camera preferences using machinelearning techniques and to tailor the automatic camera behaviour to the playerand her game-play style.Experiments show that, the novel optimisation algorithm introduced successfullyhandles highly dynamic and multi-modal tness functions such as the onestypically involved in dynamic camera control. Moreover, when applied in acommercial-standard game, the proposed automatic camera control architectureshows to be able to accurately and smoothly control the camera. Finally,the results of a user survey, conducted to evaluate the suggested methodology forcamera behaviour modelling and adaptation, shows that the resulting adaptivecinematographic experience is largely favoured by the players and it generatesa positive impact on the game performance.

M3 - Ph.D. thesis

SN - 978-87-7949-273-8

BT - Interactive Virtual Cinematography

PB - IT-Universitetet i København

ER -

ID: 39516851