Abstract
The automatic selection of good viewing parameters is very complex. In most cases, the notion of good strongly depends on the concrete application. Moreover, when an intuitive definition of good view is available, it is often difficult to establish a measure that brings it to the practice. Commonly, two kind of viewing parameters must be set: the position and orientation of the camera, and the ones relative to light sources. The first ones will determine how much of the geometry can be captured and the latter will influence on how much of it is revealed (i. e. illuminated) to the user. In this paper we will define a metric to calculate the amount of information relative to an object that is communicated to the user given a fixed camera position. This measure is based on an information-based concept, the Shannon entropy, and will be applied to the problem of automatic selection of light positions in order to adequately illuminate an object.
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Vázquez, PP., Sbert, M. (2003). Perception-Based Illumination Information Measurement and Light Source Placement. In: Kumar, V., Gavrilova, M.L., Tan, C.J.K., L’Ecuyer, P. (eds) Computational Science and Its Applications — ICCSA 2003. ICCSA 2003. Lecture Notes in Computer Science, vol 2669. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44842-X_32
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DOI: https://doi.org/10.1007/3-540-44842-X_32
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