Illumination-Invariant Video Cut-Out Using Octagon Sensitive Optimization

Zhihua Chen, Jingye Wang, Bin Sheng, Ping Li, David Dagan Feng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

This paper presents an effective video cut-out approach, which can be utilized to segment the moving object in video shots. We first introduce the Octagon-Sensitive-Filtering (OSF) and its illumination invariant feature (IIF), which is computed on each pixel of the image via adding contributions from neighboring pixels. We integrate our IIF into the variational model and obtain the seeds during preprocessing to help address large displacement and illumination changes. An effective seed update method based on tracking-then-refinement based on IIF is presented to compensate for location ambiguities, and the strategy is effective to deal with illumination variances and objects deformation. Furthermore, we apply the IIF-based graph-cut to deal with fuzzy boundaries. Multiple experiments on quantitative challenging datasets have shown the robustness, high-quality video cut-out and efficiency of our approach to acute variances of illumination and complex motion.

Original languageEnglish
Article number8658123
Pages (from-to)1410-1422
Number of pages13
JournalIEEE Transactions on Circuits and Systems for Video Technology
Volume30
Issue number5
DOIs
Publication statusPublished - May 2020
Externally publishedYes

Keywords

  • graph-cut
  • illumination-invariant
  • local features
  • seeds update
  • Video cut-out

ASJC Scopus subject areas

  • Media Technology
  • Electrical and Electronic Engineering

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