Scene categorization to indoor vs outdoor may be approached by using low-level features for inferring high-level information about the image. Low-level features such as color and texture have been used extensively in image understanding research, however, they cannot solve the problem completely. In this paper, we propose the use of a Bayesian network for integrating knowledge from low-level and midlevel features for indoor vs outdoor classification of images. Using ground truth data for sky

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... grass detection, we demonstrate that the classification performance can be significantly improved when mid-level features are employed in the classification process.