We investigate a method for learning object categories in a weakly supervised manner. Given a set of images known to contain the target category from a similar viewpoint, learning...
− We propose a vision based 3D object recognition and tracking system, which provides high level scene descriptions such as object identification and 3D pose information. The sys...
In this paper, we propose a method of object recognition and segmentation using Scale-Invariant Feature Transform (SIFT) and Graph Cuts. SIFT feature is invariant for rotations, s...
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a semisupervised manner: the model is learnt from example ...
In this paper, we present a non-rigid quasi-dense matching method and its application to object recognition and segmentation. The matching method is based on the match propagation...