We present a learning-based, sliding window-style approach for the problem of detecting humans in still images. Instead of traditional concatenation-style image location-based feat...
Probabilistic models are extensively used in medical image segmentation. Most of them employ parametric representations of densities and make idealizing assumptions, e.g. normal di...
The main purpose of this research is to develop methods for automatic identification of biological specimens in digital photographs and drawings held in a database. Incorporation ...
Y. A. Hicks, A. David Marshall, Ralph R. Martin, P...
We present a system to segment the medial edges of the vocal folds from stroboscopic video. The system has two components. The first learns a color transformation that optimally d...
Sonya Allin, John M. Galeotti, George D. Stetten, ...
We present a novel framework for learning a joint shape and appearance model from a large set of un-labelled training examples in arbitrary positions and orientations. The shape an...