Name
Abstract | ||
|---|---|---|
The analysis of inherent structures of movies plays an important role in studying stylistic devices and specific, content-related questions. Examples are the analysis of personal constellations in movie scenes, dialogue-based content analysis, or the investigation of image-based features. We provide a visual analytics approach that supports the analytical reasoning process to derive higher level insights about the content on a semantic level. Combining automatic methods for semantic scene analysis based on script and subtitle text, we perform a low-level analysis of the data automatically. Our approach features an interactive visualization that allows a multilayer interpretation of descriptive features to characterize movie content. For semantic analysis, we extract scene information from movie scripts and match them with the corresponding subtitles. With text- and image-based query techniques, we facilitate an interactive comparison of different movie scenes on an image and on a semantic level. We demonstrate how our approach can be applied for content analysis on a popular Hollywood movie. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TMM.2016.2614184 | IEEE Trans. Multimedia |
Keywords | DocType | Volume |
Motion pictures,Semantics,Data mining,Visualization,Cognition,Data visualization,Feature extraction | Journal | 18 |
Issue | ISSN | Citations |
11 | 1520-9210 | 7 |
PageRank | References | Authors |
0.74 | 33 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kuno Kurzhals | 1 | 227 | 20.63 |
| Markus John | 2 | 13 | 1.86 |
| Florian Heimerl | 3 | 252 | 15.26 |
| Paul Kuznecov | 4 | 7 | 0.74 |
| Daniel Weiskopf | 5 | 2988 | 204.30 |