TY - JOUR T1 - A “Shape Aware” Model for semi-supervised Learning of Objects and its Context JF - Proc. of NIPS Y1 - 2008 A1 - Gupta,A. A1 - Shi,J. A1 - Davis, Larry S. AB - 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 “infor- mative” background(context). We present a “shape-aware” 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. ER -