A key step for the effective use of local image features (i.e., highly distinctive and robust features) for recognition or image matching is the appropriate grouping of feature ma...
In this paper, we propose a method for extracting image features which utilizes 2 nd order statistics, i.e., spatial and orientational auto-correlations of local gradients. It enab...
We consider the use of top-points for object retrieval. These points are based on scale-space and catastrophe theory, and are invariant under gray value scaling and offset as well ...
This paper describes a novel multi-view matching framework based on a new type of invariant feature. Our features are located at Harris corners in discrete scale-space and oriente...
Matthew Brown, Richard Szeliski, Simon A. J. Winde...
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...