Automatic Video Segmentation Based on Information Centroid and Optimized SaliencyCut

Hui Si Wu, Meng Shu Liu, Lu Lu Yin, Ping Li, Zhen Kun Wen, Hon Cheng Wong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

We propose an automatic video segmentation method based on an optimized SaliencyCut equipped with information centroid (IC) detection according to level balance principle in physical theory. Unlike the existing methods, the image information of another dimension is provided by the IC to enhance the video segmentation accuracy. Specifically, our IC is implemented based on the information-level balance principle in the image, and denoted as the information pivot by aggregating all the image information to a point. To effectively enhance the saliency value of the target object and suppress the background area, we also combine the color and the coordinate information of the image in calculating the local IC and the global IC in the image. Then saliency maps for all frames in the video are calculated based on the detected IC. By applying IC smoothing to enhance the optimized saliency detection, we can further correct the unsatisfied saliency maps, where sharp variations of colors or motions may exist in complex videos. Finally, we obtain the segmentation results based on IC-based saliency maps and optimized SaliencyCut. Our method is evaluated on the DAVIS dataset, consisting of different kinds of challenging videos. Comparisons with the state-of-the-art methods are also conducted to evaluate our method. Convincing visual results and statistical comparisons demonstrate its advantages and robustness for automatic video segmentation.

Original languageEnglish
Pages (from-to)564-575
Number of pages12
JournalJournal of Computer Science and Technology
Volume35
Issue number3
DOIs
Publication statusPublished - 1 May 2020

Keywords

  • automatic video segmentation
  • information centroid
  • optimized SaliencyCut
  • saliency detection

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computer Science Applications
  • Computational Theory and Mathematics

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