Dichromatic model based temporal color constancy for AC light sources

Jun Sang Yoo, Jong Ok Kim

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

19 Citations (Scopus)

Abstract

Existing dichromatic color constancy approach commonly requires a number of spatial pixels which have high specularity. In this paper, we propose a novel approach to estimate the illuminant chromaticity of AC light source using high-speed camera. We found that the temporal observations of an image pixel at a fixed location distribute on an identical dichromatic plane. Instead of spatial pixels with high specularity, multiple temporal samples of a pixel are exploited to determine AC pixels for dichromatic plane estimation, whose pixel intensity is sinusoidally varying well. A dichromatic plane is calculated per each AC pixel, and illuminant chromaticity is determined by the intersection of dichromatic planes. From multiple dichromatic planes, an optimal illuminant is estimated with a novel MAP framework. It is shown that the proposed method outperforms both existing dichromatic based methods and temporal color constancy methods, irrespective of the amount of specularity.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
PublisherIEEE Computer Society
Pages12321-12330
Number of pages10
ISBN (Electronic)9781728132938
DOIs
Publication statusPublished - 2019 Jun
Event32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019 - Long Beach, United States
Duration: 2019 Jun 162019 Jun 20

Publication series

NameProceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Volume2019-June
ISSN (Print)1063-6919

Conference

Conference32nd IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2019
Country/TerritoryUnited States
CityLong Beach
Period19/6/1619/6/20

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

Keywords

  • Computer Vision Theory
  • Low-level Vision

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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