86 citations · 181 across the 6 of their papers we have counts for
7 papers
High Dimensional Data Modeling Techniques for Detection of Chemical Plumes and Anomalies in Hyperspectral Images and Movies
Yi, Wang, Guangliang Chen +1
We briefly review recent progress in techniques for modeling and analyzing hyperspectral images and movies, in particular for detecting plumes of both known and unknown chemicals.…
Guaranteed sparse signal recovery with highly coherent sensing matrices
Guangliang Chen, Atul Divekar, Deanna Needell
Compressive sensing is a methodology for the reconstruction of sparse or compressible signals using far fewer samples than required by the Nyquist criterion. However, many of the r…
Multiscale Geometric Methods for Data Sets II: Geometric Multi-Resolution Analysis
William K. Allard, Guangliang Chen, Mauro Maggioni
Data sets are often modeled as point clouds in , for large. It is often assumed that the data has some interesting low-dimensional structure, for example that of a -dim…
Spectral clustering based on local linear approximations
Ery Arias-Castro, Guangliang Chen, Gilad Lerman
In the context of clustering, we assume a generative model where each cluster is the result of sampling points in the neighborhood of an embedded smooth surface; the sample may be…
Motion Segmentation by SCC on the Hopkins 155 Database
G. Chen, G. Lerman
We apply the Spectral Curvature Clustering (SCC) algorithm to a benchmark database of 155 motion sequences, and show that it outperforms all other state-of-the-art methods. The ave…
Kernel Spectral Curvature Clustering (KSCC)
G. Chen, S. Atev, G. Lerman
Multi-manifold modeling is increasingly used in segmentation and data representation tasks in computer vision and related fields. While the general problem, modeling data by mixtur…
Foundations of a Multi-way Spectral Clustering Framework for Hybrid Linear Modeling
Guangliang Chen, Gilad Lerman
The problem of Hybrid Linear Modeling (HLM) is to model and segment data using a mixture of affine subspaces. Different strategies have been proposed to solve this problem, however…