A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
Background: CRANKITE is a suite of programs for simulating backbone conformations of polypeptides and proteins. The core of the suite is an efficient Metropolis Monte Carlo sample...
The use of local features in computer vision has shown to be promising. Local features have several advantages including invariance to image transformations, independence of the ba...
This paper presents a robust object tracking method via a spatial bias appearance model learned dynamically in video. Motivated by the attention shifting among local regions of a ...
Many approaches have been proposed to locate faces in an image. There are, however, two problems in previous facial shape models using feature points. First, the dimension of the s...