In the problem of probability forecasting the learner’s goal is to output, given a training set and a new object, a suitable probability measure on the possible values of the ne...
The FERET evaluation compared recognition rates for different semi-automated and automated face recognition algorithms. We extend FERET by considering when differences in recognit...
J. Ross Beveridge, Kai She, Bruce A. Draper, Geof ...
We present an object recognition algorithm that uses model and image line features to locate complex objects in high clutter environments. Finding correspondences between model an...
Face localization is the process of finding the exact position of a face in a given image. This can be useful in several applications such as face tracking or person authenticatio...
Recent works in object recognition often use visual words, i.e. vector quantized local descriptors extracted from the images. In this paper we present a novel method to build such ...