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Cinemetrics: Creative Approaches to Visualize and Analyze Movie Data
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Dissertation
Cinemetrics: Creative Approaches to Visualize and Analyze Movie Data
2021
Overview
In the age of visual media that we live in, there is an immensity of content being produced worldwide every day through the cinematographic and TV industries. This, alongside with the widespread availability of Internet access and social media, has democratized the appreciation, discussion and constant analyses of movies and TV shows. Since these are visual media with their own “visual language”, where creators use a lot of visual tricks to convey information, emotion, and to show a bit of their signature style, a lot of data can be extracted from them. This represents a great potential for people trying to analyze trends and patterns in video content, for example with colour palettes, length of shots, movement in scenes, audio, etc. But all this can be overwhelming without the aid of technology, and so there has also been a growth in the development of tools based in Artificial Intelligence, and Machine and Deep Learning, to be able to quickly and efficiently analyse this data and produce meaningful and insightful results that might help in the creation of new video-based media or just for anyone interested in video, like cinematographers, video editors, animators or any others. However, with large amounts of data, the results can sometimes be hard to parse by the user, and so there’s also been a trend of trying to consolidate data into graphic representations for easier analysis, giving rise to a new field called Data Visualization. With this in mind, we attempted to develop a new tool for video analysis of multimedia files based in scripts that would be able to give information about the composition of shots and scenes, such as the instants of the cuts or estimates of numbers like the total of shots, frames and more, but also to graphically present information using multimedia data visualizations.
Publisher
ProQuest Dissertations & Theses
Subject
ISBN
9798352994276
