This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
Kamal Nigam, Andrew McCallum, Sebastian Thrun, Tom...
This paper forms a continuation of our work focused on exploiting film grammar for the task of automated film understanding. We examine film rhythm, a powerful narrative concept u...
In order to track and recognize the movements of multiple people using multiple cameras, each person needs to be segmented and identified in the image of each camera. We propose a...
An important and unsolved problem today is the automatic quantification of the quality of video flows transmitted over packet networks. In particular, the ability to perform this ...
Abstract--We propose an approach to accurately detecting twodimensional (2-D) shapes. The cross section of the shape boundary is modeled as a step function. We first derive a one-d...