Spiralet Sparse Representation
Computer Vision and Pattern Recognition
2014-04-16 v1
Abstract
This is the first report on Working Paper WP-RFM-14-01. The potential and capability of sparse representations is well-known. However, their (multivariate variable) vectorial form, which is completely fine in many fields and disciplines, results in removal and filtering of important "spatial" relations that are implicitly carried by two-dimensional [or multi-dimensional] objects, such as images. In this paper, a new approach, called spiralet sparse representation, is proposed in order to develop an augmented representation and therefore a modified sparse representation and theory, which is capable to preserve the data associated to the spatial relations.
Cite
@article{arxiv.1404.3991,
title = {Spiralet Sparse Representation},
author = {Reza Farrahi Moghaddam and Mohamed Cheriet},
journal= {arXiv preprint arXiv:1404.3991},
year = {2014}
}
Comments
10 pages, Working Paper Number: WP-RFM-14-01