Illumination-robust variational optical flow using cross-correlation

József Molnár, Dmitry Chetverikov, Sándor Fazekas

Research output: Contribution to journalArticle

29 Citations (Scopus)


We address the problem of variational optical flow for video processing applications that need fast operation and robustness to drastic variations in illumination. Recently, a solution [1] has been proposed based on the photometric invariants of the dichromatic reflection model [2]. However, this solution is only applicable to colour videos with brightness variations. Greyscale videos, or colour videos with colour illumination changes cannot be adequately handled. We propose two illumination-robust variational methods based on cross-correlation that are applicable to colour and grey-level sequences and robust to brightness and colour illumination changes. First, we present a general implicit nonlinear scheme that assumes no particular analytical form of energy functional and can accommodate different image components and data metrics, including cross-correlation. We test the nonlinear scheme on standard synthetic data with artificial brightness and colour effects added and conclude that cross-correlation is robust to both kinds of illumination changes. Then we derive a fast linearised numerical scheme for cross-correlation based variational optical flow. We test the linearised algorithm on challenging data and compare it to a number of state-of-the-art variational flow methods.

Original languageEnglish
Pages (from-to)1104-1114
Number of pages11
JournalComputer Vision and Image Understanding
Issue number10
Publication statusPublished - Oct 1 2010


  • Cross-correlation
  • Illumination-robustness
  • Variational optical flow

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition

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