Recent advent of graph signal processing (GSP) has spurred intensive studies of signals
that live naturally on irregular data kernels described by graphs (eg, social networks …

Piecewise smooth (PWS) images (eg, depth maps or animation images) contain unique
signal characteristics such as sharp object boundaries and slowly varying interior surfaces …

This paper extends previous results on wavelet filterbanks for data defined on graphs from
the case of orthogonal transforms to more general and flexible biorthogonal transforms. As …

Geometric data acquired from real-world scenes, eg, 2D depth images, 3D point clouds, and
4D dynamic point clouds, have found a wide range of applications including immersive …

In image compression, classical block-based separable transforms tend to be inefficient
when image blocks contain arbitrarily shaped discontinuities. For this reason, transforms …

To compactly represent a graph signal in the frequency domain, critically sampled
biorthogonal wavelet filterbanks have been proposed to decompose signals on bipartite …

In our recent work, we proposed the construction of critically-sampled wavelet filterbanks for
analyzing functions defined on the vertices of arbitrary undirected graphs. These graph …

In this paper, we propose a new graph-based transform and illustrate its potential
application to signal compression. Our approach relies on the careful design of a graph that …

This paper addresses the problem of energy compaction of dense 4D light fields by
designing geometry-aware local graph-based transforms. Local graphs are constructed on …

We present spectral graph skeletons (SGS), a novel graph-based method for action
recognition from depth cameras. The contribution of this paper is to leverage a spectral …