A study on non-static environment, flow field and splitting formation in FAME
Flocks are often used to describe a cluster of animals or particles. In computer animations, flocks behaviours are studied extensively and simulations were built upon it. Flock simulations are gathering much interest in recent years, especially in the entertainment industry where this technology can...
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sg-ntu-dr.10356-520262023-03-03T20:45:52Z A study on non-static environment, flow field and splitting formation in FAME Seow, Yi Fan. Ong Yew Soon School of Computer Engineering Centre for Computational Intelligence DRNTU::Engineering::Computer science and engineering Flocks are often used to describe a cluster of animals or particles. In computer animations, flocks behaviours are studied extensively and simulations were built upon it. Flock simulations are gathering much interest in recent years, especially in the entertainment industry where this technology can greatly reduce the time and production cost. The Flocking Animation and Modelling Environment (FAME) is a technology developed by Centre for Computational Intelligence (C2I) in NTU. It aims to automate multiple agents in real-time, reacting together as a flock. They have enjoyed some success with Dark Dot. Despite that, much more can be done into FAME to widen and enrich its application towards different genre of games. This project studies on trends and various aspects of games and identify core functionality that is often seen. Then comparing it to FAME, areas of improvement or implementation can be identified such that it the FAME library can be further enhanced to be more dynamic and easier for developers to use. Finally, a game created from this project will be used to demonstrate the application of FAME in games, as well as the improvised features done through the project. Bachelor of Engineering (Computer Science) 2013-04-19T05:10:31Z 2013-04-19T05:10:31Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/52026 en Nanyang Technological University 63 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Seow, Yi Fan. A study on non-static environment, flow field and splitting formation in FAME |
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Flocks are often used to describe a cluster of animals or particles. In computer animations, flocks behaviours are studied extensively and simulations were built upon it. Flock simulations are gathering much interest in recent years, especially in the entertainment industry where this technology can greatly reduce the time and production cost. The Flocking Animation and Modelling Environment (FAME) is a technology developed by Centre for Computational Intelligence (C2I) in NTU. It aims to automate multiple agents in real-time, reacting together as a flock. They have enjoyed some success with Dark Dot. Despite that, much more can be done into FAME to widen and enrich its application towards different genre of games. This project studies on trends and various aspects of games and identify core functionality that is often seen. Then comparing it to FAME, areas of improvement or implementation can be identified such that it the FAME library can be further enhanced to be more dynamic and easier for developers to use. Finally, a game created from this project will be used to demonstrate the application of FAME in games, as well as the improvised features done through the project. |
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Ong Yew Soon |
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Ong Yew Soon Seow, Yi Fan. |
format |
Final Year Project |
author |
Seow, Yi Fan. |
author_sort |
Seow, Yi Fan. |
title |
A study on non-static environment, flow field and splitting formation in FAME |
title_short |
A study on non-static environment, flow field and splitting formation in FAME |
title_full |
A study on non-static environment, flow field and splitting formation in FAME |
title_fullStr |
A study on non-static environment, flow field and splitting formation in FAME |
title_full_unstemmed |
A study on non-static environment, flow field and splitting formation in FAME |
title_sort |
study on non-static environment, flow field and splitting formation in fame |
publishDate |
2013 |
url |
http://hdl.handle.net/10356/52026 |
_version_ |
1759856356207099904 |