Video object segmentation based on superpixel trajectories

Mohamed A. Abdelwahab, Moataz M. Abdelwahab, Hideaki Uchiyama, Atsushi Shimada, Rin Ichiro Taniguchi

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

2 Citations (Scopus)


In this paper, a video object segmentation method utilizing the motion of superpixel centroids is proposed. Our method achieves the same advantages of methods based on clustering point trajectories, furthermore obtaining dense clustering labels from sparse ones becomes very easy. Simply for each superpixel the label of its centroid is propagated to all its entire pixels. In addition to the motion of superpixel centroids, histogram of oriented optical flow, HOOF, extracted from superpixels is used as a second feature. After segmenting each object, we distinguish between foreground objects and the background utilizing the obtained clustering results.

Original languageEnglish
Title of host publicationImage Analysis and Recognition - 13th International Conference, ICIAR 2016, Proceedings
EditorsAurelio Campilho, Aurelio Campilho, Fakhri Karray
PublisherSpringer Verlag
Number of pages7
ISBN (Print)9783319415000
Publication statusPublished - 2016
Event13th International Conference on Image Analysis and Recognition, ICIAR 2016 - Povoa de Varzim, Portugal
Duration: Jul 13 2016Jul 16 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other13th International Conference on Image Analysis and Recognition, ICIAR 2016
CityPovoa de Varzim

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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