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Describing Visual Scenes Using Transformed Objects and Parts
2007
International Journal of Computer Vision
We develop hierarchical, probabilistic models for objects, the parts composing them, and the visual scenes surrounding them. Our approach couples topic models originally developed for text analysis with spatial transformations, and thus consistently accounts for geometric constraints. By building integrated scene models, we may discover contextual relationships, and better exploit partially labeled training images. We first consider images of isolated objects, and show that sharing parts among
doi:10.1007/s11263-007-0069-5
fatcat:gcwozuh44rapbmufuewiqxdmhe