Separation of Reflection Components by Sparse Non-Negative Matrix Factorization

Yasuhiro Akashi, Takayuki Okatani

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

4 Citations (Scopus)

Abstract

This paper presents a novel method for separating reflection components in a single image based on the dichromatic reflection model. Our method is based on a modified version of sparse non-negative matrix factorization (NMF). It simultaneously performs the estimation of body colors and the separation of reflection components through optimization. Our method does not use a spatial prior such as smoothness of colors on the object surface, which is in contrast with recent methods attempting to use such priors to improve separation accuracy. Experimental results show that as compared with these recent methods that use priors, our method is more accurate and robust. For example, it can better deal with difficult cases such as the case where a body color is close to the illumination color.

Original languageEnglish
Title of host publicationComputer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Revised Selected Papers
EditorsDaniel Cremers, Hideo Saito, Ian Reid, Ming-Hsuan Yang
PublisherSpringer Verlag
Pages611-625
Number of pages15
ISBN (Electronic)9783319168135
DOIs
Publication statusPublished - 2015
Event12th Asian Conference on Computer Vision, ACCV 2014 - Singapore, Singapore
Duration: 2014 Nov 12014 Nov 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9007
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th Asian Conference on Computer Vision, ACCV 2014
CountrySingapore
CitySingapore
Period14/11/114/11/5

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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