Scene appearance model based on spatial prediction

The appearance of a static scene as sensed by a camera changes considerably as a result of changes in the illumination that falls upon it. Scene appearance modeling is thus necessary for understanding which changes in the appearance of a scene are the result of illumination changes. For any camera,...

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Bibliographic Details
Main Author: Hagege, Rami Rahamim (Contributor)
Other Authors: Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Springer Berlin Heidelberg, 2016-10-21T22:09:38Z.
Subjects:
Online Access:Get fulltext
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100 1 0 |a Hagege, Rami Rahamim  |e author 
100 1 0 |a Massachusetts Institute of Technology. Laboratory for Information and Decision Systems  |e contributor 
100 1 0 |a Hagege, Rami Rahamim  |e contributor 
245 0 0 |a Scene appearance model based on spatial prediction 
260 |b Springer Berlin Heidelberg,   |c 2016-10-21T22:09:38Z. 
856 |z Get fulltext  |u http://hdl.handle.net/1721.1/104930 
520 |a The appearance of a static scene as sensed by a camera changes considerably as a result of changes in the illumination that falls upon it. Scene appearance modeling is thus necessary for understanding which changes in the appearance of a scene are the result of illumination changes. For any camera, the appearance of the scene is a function of the illumination sources in the scene, the three-dimensional configuration of the objects in the scene and the reflectance properties of all the surfaces in the scene. A scene appearance model is described here as a function of the behavior of static illumination sources, within or beyond the scene, and arbitrary three-dimensional configurations of patches and their reflectance distributions. Based on the suggested model, a spatial prediction technique was developed to predict the appearance of the scene, given a few measurements within it. The scene appearance model and the prediction technique were developed analytically and tested empirically. Two potential applications are briefly explored. 
546 |a en 
655 7 |a Article 
773 |t Machine Vision and Applications