TY - GEN
T1 - Separation of Reflection Components by Sparse Non-Negative Matrix Factorization
AU - Akashi, Yasuhiro
AU - Okatani, Takayuki
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Number 25135701.
Publisher Copyright:
© Springer International Publishing Switzerland 2015.
PY - 2015
Y1 - 2015
N2 - 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.
AB - 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.
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U2 - 10.1007/978-3-319-16814-2_40
DO - 10.1007/978-3-319-16814-2_40
M3 - Conference contribution
AN - SCOPUS:84929629176
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 611
EP - 625
BT - Computer Vision - ACCV 2014 - 12th Asian Conference on Computer Vision, Revised Selected Papers
A2 - Cremers, Daniel
A2 - Saito, Hideo
A2 - Reid, Ian
A2 - Yang, Ming-Hsuan
PB - Springer Verlag
T2 - 12th Asian Conference on Computer Vision, ACCV 2014
Y2 - 1 November 2014 through 5 November 2014
ER -