Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Model-based image recognition requires a general model of the object that should be detected in an image. In many applications such models are not known a-priori instead of they mu...
To segregate overlapping objects into depth layers requires the integration of local occlusion cues distributed over the entire image into a global percept. We propose to model thi...
Learning a new object class from cluttered training images is very challenging when the location of object instances is unknown. Previous works generally require objects covering a...
common features in all learning objects only. The In this paper, we propose two methods of clustering learning images to generate prototypes automatically for object recognition. O...