@article {13134,
	title = {A {\textquotedblleft}Shape Aware{\textquotedblright} Model for semi-supervised Learning of Objects and its Context},
	journal = {Proc. of NIPS},
	year = {2008},
	month = {2008///},
	abstract = {We present an approach that combines bag-of-words and spatial models to performsemantic and syntactic analysis for recognition of an object based on its internal
appearance and its context. We argue that while object recognition requires mod-
eling relative spatial locations of image features within the object, a bag-of-word
is sufficient for representing context. Learning such a model from weakly labeled
data involves labeling of features into two classes: foreground(object) or {\textquotedblleft}infor-
mative{\textquotedblright} background(context). We present a {\textquotedblleft}shape-aware{\textquotedblright} model which utilizes
contour information for efficient and accurate labeling of features in the image.
Our approach iterates between an MCMC-based labeling and contour based la-
beling of features to integrate co-occurrence of features and shape similarity.
},
	author = {Gupta,A. and Shi,J. and Davis, Larry S.}
}
