Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
In this paper we address the problem of minimizing a large class of energy functions that occur in early vision. The major restriction is that the energy function's smoothnes...
Abstract—High computational effort in modern image processing applications like medical imaging or high-resolution video processing often demands for massively parallel special p...
Joachim Keinert, Hritam Dutta, Frank Hannig, Chris...
Applications augmented with adaptive capabilities are becoming common in parallel computing environments which share resources such as main memory, network, or disk I/O. For large...
Nurzhan Ustemirov, Masha Sosonkina, Mark S. Gordon...
Robust local image features have been used successfully in robot localization and camera pose estimation; region tracking using affine warps is considered state of the art also for...