Sparse representation based classification with intra-class variation dictionary on symmetric positive definite manifolds

Hiroyuki Kasai, Kohei Yoshikawa

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Sparse representation based classification (SRC) using training samples as a dictionary has engendered promising results for many computer vision tasks. However, although the SRC classifier exhibits very competitive performances when given sufficient training samples of each class, it presents the difficulty that its performance decreases considerably when fewer training samples are used. As described herein, we propose a Riemannian SRC with intra-class variation dictionary on SPD matrices, R-ESRC. The key challenge is establishment of a mathematically correct intra-class variation dictionary in terms of geometry of SPD manifold. To this end, we exploit the geometric mean calculation and the logarithm mapping. Numerical evaluations demonstrate the superior performance of our proposed algorithm.

Original languageEnglish
Title of host publication2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages255-258
Number of pages4
ISBN (Electronic)9781538646625
DOIs
Publication statusPublished - 2018 Jun 18
Externally publishedYes
Event17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 - Bilbao, Spain
Duration: 2017 Dec 182017 Dec 20

Publication series

Name2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017

Conference

Conference17th IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017
CountrySpain
CityBilbao
Period17/12/1817/12/20

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Energy Engineering and Power Technology
  • Computer Networks and Communications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Signal Processing

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  • Cite this

    Kasai, H., & Yoshikawa, K. (2018). Sparse representation based classification with intra-class variation dictionary on symmetric positive definite manifolds. In 2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017 (pp. 255-258). (2017 IEEE International Symposium on Signal Processing and Information Technology, ISSPIT 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISSPIT.2017.8388651