We compare different statistical characterizations of a set of strings, for three different histogram-based distances. Given a distance, a set of strings may be characterized by it...
Kernel methods yield state-of-the-art performance in certain applications such as image classification and object detection. However, large scale problems require machine learning...
Sreekanth Vempati, Andrea Vedaldi, Andrew Zisserma...
One of the most widely used approaches in the context of object recognition across illumination changes consists in comparing the images by means of the intersection between invar...
In this paper we extend a method that uses image patch histograms and discriminative training to recognize objects in cluttered scenes. The method generalizes and performs well for...
Invariant feature descriptors such as SIFT and GLOH have been demonstrated to be very robust for image matching and object recognition. However, such descriptors are typically of ...