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Outdoor scene classification is challenging due to irregular geometry, uncontrolled illumination, and noisy reflectance distributions. This paper discusses a Bayesian approach to classifying a color image of an outdoor scene. A likelihood model factors in the physics of the image formation process, the sensor noise distribution, and prior distributions over geometry, material types, and illuminant spectrum parameters. These prior distributions are learned through a training process that usesdoi:10.1109/cvpr.2001.990658 dblp:conf/cvpr/TsinCRK01 fatcat:jxcu42swabayplubjqyyg6ik2q