In this paper, we consider the problem of projective reconstruction based on the subspace method. Unlike existing subspace methods which require that all the points are visible in...
Abstract. Subspace mapping methods aim at projecting high-dimensional data into a subspace where a specific objective function is optimized. Such dimension reduction allows the re...
Axel J. Soto, Marc Strickert, Gustavo E. Vazquez, ...
Subspace learning techniques are widespread in pattern recognition research. They include Principal Component Analysis (PCA), Locality Preserving Projection (LPP), etc. These tech...
We present a method for removing environmental noise from physiological recordings such as Magnetoencephalography (MEG) for which noise-sensitive reference channels are available....
With the recent availability of commercial light field cameras, we can foresee a future in which light field signals will be as common place as images. Hence, there is an immine...