Locally linear embedding (LLE) is one of the most well-known manifold learning methods.
As the representative linear extension of LLE, orthogonal neighborhood preserving …

Light Field (LF) imaging is a promising solution for providing more immersive and closer to
reality multimedia experiences to end-users with unprecedented creative freedom and …

Light field imaging is a promising new technology that allows the user not only to change the
focus and perspective after taking a picture, as well as to generate 3D content, among other …

This paper describes a set of neural network architectures, called Prediction Neural
Networks Set (PNNS), based on both fully-connected and convolutional neural networks, for …

Holoscopic imaging is a prospective acquisition and display solution for providing true 3D
content and fatigue-free 3D visualization. However, efficient coding schemes for this …

Abstract 3D holoscopic image, also known as integral imaging, light field imaging and
plenoptic imaging, can provide a natural and fatigue-free 3D visualization. However, a large …

Exemplar-based inpainting methods involve three critical steps: finding the patch processing
order, searching for best matching patches, and estimating the unknown pixels from the best …

This paper describes a video inpainting algorithm based on motion-compensated neighbor
embedding. The unknown pixels are estimated as a linear combination of the K closest …

This paper proposes a dictionary-based L1-norm sparse coding for time series prediction
which requires no training phase, and minimal parameter tuning, making it suitable for …

This paper describes new image prediction methods based on neighbor embedding (NE)
techniques. Neighbor embedding methods are used here to approximate an input block (the …