We propose a framework for general multiple target tracking, where the input is a set of candidate regions in each frame, as obtained from a state of the art background learning, ...
Recent years have witnessed an increasing number of studies in stream mining, which aim at building an accurate model for continuously arriving data. Somehow most existing work ma...
In spite of the popularity of probabilistic mixture models for latent structure discovery from data, mixture models do not have a natural mechanism for handling sparsity, where ea...
We present a semi-supervised machine-learning approach for the classification of adjectives into property- vs. relationdenoting adjectives, a distinction that is highly relevant f...
—We present a discriminative part-based approach for human action recognition from video sequences using motion features. Our model is based on the recently proposed hidden condi...