We present an integrated framework for learning asymmetric boosted classifiers and online learning to address the problem of online learning asymmetric boosted classifiers, which ...
We propose and test an objective criterion for evaluation of clustering performance: How well does a clustering algorithm run on unlabeled data aid a classification algorithm? The...
Recognition of 3D objects from different viewpoints is a difficult problem. In this paper, we propose a new method to recognize 3D range images by matching local surface descripto...
In this paper we present a mixture density based approach to invariant image object recognition. We start our experiments using Gaussian mixture densities within a Bayesian classi...
In this paper, we propose an original approach for content-based video indexing and retrieval. It relies on the tracking of entities of interest and the analysis of their apparent...