Dimensionality reduction plays an important role in many machine learning and pattern recognition tasks. In this paper, we present a novel dimensionality reduction algorithm calle...
For learning purposes, representations of real world objects can be built by using the concept of dissimilarity (distance). In such a case, an object is characterized in a relative...
One fundamental task in near-neighbor search as well as other similarity matching efforts is to find a distance function that can efficiently quantify the similarity between two o...
This paper introduces BoostMap, a method that can significantly reduce retrieval time in image and video database systems that employ computationally expensive distance measures, ...
Vassilis Athitsos, Jonathan Alon, Stan Sclaroff, G...
Covariance matrices have recently been a popular choice for versatile tasks like recognition and tracking due to their powerful properties as local descriptor and their low comput...