Temporally object-based video co-segmentation

Michael Ying Yang, Matthias Reso*, Jun Tang, Wentong Liao, Bodo Rosenhahn

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)

Abstract

In this paper, we propose an unsupervised video object co-segmentation framework based on the primary object proposals to extract the common foreground object(s) from a given video set. In addition to the objectness attributes and motion coherence our framework exploits the temporal consistency of the object-like regions between adjacent frames to enrich the original set of object proposals. We call the enriched proposal sets temporal proposal streams, as they are composed of the most similar proposals from each frame augmented with predicted proposals using temporally consistent superpixel information. The temporal proposal streams represent all the possible region tubes of the objects. Therefore, we formulate a graphical model to select a proposal stream for each object in which the pairwise potentials consist of the appearance dissimilarity between different streams in the same video and also the similarity between the streams in different videos. This model is suitable for single (multiple) foreground objects in two (more) videos, which can be solved by any existing energy minimization method. We evaluate our proposed framework by comparing it to other video co-segmentation algorithms. Our method achieves improved performance on state-of-the-art benchmark datasets.

Original languageEnglish
Title of host publicationAdvances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings
EditorsMark Elendt, Richard Boyle, Eric Ragan, Bahram Parvin, Rogerio Feris, Tim McGraw, Ioannis Pavlidis, Regis Kopper, George Bebis, Darko Koracin, Zhao Ye, Gunther Weber
Place of PublicationLas Vegas
PublisherSpringer Verlag
Pages198-209
Number of pages12
ISBN (Print)9783319278568
DOIs
Publication statusPublished - 18 Dec 2015
Externally publishedYes
Event11th International Symposium on Visual Computing, ISVC 2015 - Las Vegas, United States
Duration: 14 Dec 201516 Dec 2015
Conference number: 11

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9474
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Symposium on Visual Computing, ISVC 2015
Abbreviated titleISVC
CountryUnited States
CityLas Vegas
Period14/12/1516/12/15

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  • Cite this

    Yang, M. Y., Reso, M., Tang, J., Liao, W., & Rosenhahn, B. (2015). Temporally object-based video co-segmentation. In M. Elendt, R. Boyle, E. Ragan, B. Parvin, R. Feris, T. McGraw, I. Pavlidis, R. Kopper, G. Bebis, D. Koracin, Z. Ye, ... G. Weber (Eds.), Advances in Visual Computing - 11th International Symposium, ISVC 2015, Proceedings (pp. 198-209). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9474). Las Vegas: Springer Verlag. https://doi.org/10.1007/978-3-319-27857-5_18