Maximum entropy light source placement
Finding the "best" viewing parameters for a scene is quite difficult but a very important problem. Fully automatic procedures seem to be impossible as the notion of "best" strongly depends on the human judgment as well as on the application. In this paper a solution to the sub-pr...
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| Veröffentlicht in: | 13th IEEE Visualization 2002 Conference (VIS 2002) S. 275 - 282 |
|---|---|
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| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
Washington, DC, USA
IEEE Computer Society
27.10.2002
IEEE |
| Schriftenreihe: | ACM Conferences |
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| ISBN: | 9780780374980, 0780374983 |
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| Abstract | Finding the "best" viewing parameters for a scene is quite difficult but a very important problem. Fully automatic procedures seem to be impossible as the notion of "best" strongly depends on the human judgment as well as on the application. In this paper a solution to the sub-problem of placing light sources for given camera parameters is proposed. A light position is defined to be optimal, when the resulting illumination reveals more about the scene as the illuminations from all other light positions, i.e. the light position maximizes the information that is added to the image through the illumination. With the help of an experiment with several subjects we could adapt the information measure to the actually perceived information content. We present fast global optimization procedures and solutions for two and more light sources. |
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| AbstractList | Finding the "best" viewing parameters for a scene is quite difficult but a very important problem. Fully automatic procedures seem to be impossible as the notion of "best" strongly depends on the human judgment as well as on the application. In this paper a solution to the sub-problem of placing light sources for given camera parameters is proposed. A light position is defined to be optimal, when the resulting illumination reveals more about the scene as the illuminations from all other light positions, i.e. the light position maximizes the information that is added to the image through the illumination. With the help of an experiment with several subjects we could adapt the information measure to the actually perceived information content. We present fast global optimization procedures and solutions for two and more light sources. |
| Author | Gumhold, Stefan |
| Author_xml | – sequence: 1 givenname: Stefan surname: Gumhold fullname: Gumhold, Stefan organization: WSI/GRIS, University of Tübingen |
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| Keywords | maximum entropy visualization illumination optimization user study lighting design Visualization Computer graphics Illumination Global optimum Entropy Method of maximum entropy Optimization Light sources |
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| SubjectTerms | Applied computing -- Document management and text processing -- Document capture -- Graphics recognition and interpretation Applied sciences Artificial intelligence Computer science; control theory; systems Computing methodologies -- Computer graphics Exact sciences and technology Mathematics of computing -- Mathematical analysis -- Mathematical optimization Pattern recognition. Digital image processing. Computational geometry Theory of computation -- Design and analysis of algorithms -- Mathematical optimization |
| Title | Maximum entropy light source placement |
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