Design of Non-Linear Kernel Dictionaries for Object Recognition

Volume: 22, Issue: 12, Pages: 5123 - 5135
Published: Dec 1, 2013
Abstract
In this paper, we present dictionary learning methods for sparse signal representations in a high dimensional feature space. Using the kernel method, we describe how the well known dictionary learning approaches, such as the method of optimal directions and KSVD, can be made nonlinear. We analyze their kernel constructions and demonstrate their effectiveness through several experiments on classification problems. It is shown that nonlinear...
Paper Details
Title
Design of Non-Linear Kernel Dictionaries for Object Recognition
Published Date
Dec 1, 2013
Volume
22
Issue
12
Pages
5123 - 5135
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.