3 accepted papers
We present a novel egocentric visual localization algorithm for an indoor navigation system, called PERCEPT -V, which is designed to assist the blind and visually impaired users traveling independently in an unfamiliar indoor space. Through the integration of a background extraction module based on…
The literature on compressive parameter estimation has been mostly focused on the use of sparsity dictionaries that encode a sampling of the parameter space; these dictionaries, however, suffer from coherence issues that must be controlled for successful estimation. We propose the use of statistical…
We consider the problem of selecting a subset of the dimensions of an image manifold that best preserves the underlying local structure in the original data. We have previously shown that masks which preserve the data neighborhood graph are well suited to global manifold learning algorithms. However…