Current methods for learning visual categories work well when a large amount of labeled data is available, but can run into severe difficulties when the number of labeled examples...
In this paper, we propose a new manifold representation capable of being applied for visual speech recognition. In this regard, the real time input video data is compressed using P...
Dahai Yu, Ovidiu Ghita, Alistair Sutherland, Paul ...
- This paper presents a neurologically inspired vergence control model that uses the optimization of the disparity error between interlaced cortical maps incident on the visual cor...
Many of the available image databases have keyword annotations associated with the images. In spite of the availability of good quality low-level visual features that reflect wel...
This paper deals with the problem of analyzing and visualizing volume data sets of large size. To this aim, we define a three-dimensional multi-resolution model based on unstruct...