Sequential clique optimization for video object segmentation

Yeong Jun Koh; Young Yoon Lee; Chang-Su Kim

doi:10.1007/978-3-030-01264-9_32

Sequential clique optimization for video object segmentation

Yeong Jun Koh, Young Yoon Lee, Chang-Su Kim

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Citations (Scopus)

Abstract

A novel algorithm to segment out objects in a video sequence is proposed in this work. First, we extract object instances in each frame. Then, we select a visually important object instance in each frame to construct the salient object track through the sequence. This can be formulated as finding the maximal weight clique in a complete k-partite graph, which is NP hard. Therefore, we develop the sequential clique optimization (SCO) technique to efficiently determine the cliques corresponding to salient object tracks. We convert these tracks into video object segmentation results. Experimental results show that the proposed algorithm significantly outperforms the state-of-the-art video object segmentation and video salient object detection algorithms on recent benchmark datasets.

Original language	English
Title of host publication	Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
Editors	Vittorio Ferrari, Cristian Sminchisescu, Yair Weiss, Martial Hebert
Publisher	Springer Verlag
Pages	537-556
Number of pages	20
ISBN (Print)	9783030012632
DOIs	https://doi.org/10.1007/978-3-030-01264-9_32
Publication status	Published - 2018
Event	15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany Duration: 2018 Sept 8 → 2018 Sept 14

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11218 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	15th European Conference on Computer Vision, ECCV 2018
Country/Territory	Germany
City	Munich
Period	18/9/8 → 18/9/14

Bibliographical note

Funding Information:
Acknowledgement. This work was supported partly by the Ministry of Science and ICT (MSIT), Korea, under the Information Technology Research Center (ITRC) support program (IITP-2018-2016-0-00464) supervised by the Institute for Information & communications Technology Promotion, and the National Research Foundations of Korea (NRF) grant funded by the Korea government (MSIP) (No. NRF-2015R1A2A1A10055037 and No. NRF-2018R1A2B3003896).

Publisher Copyright:
© 2018, Springer Nature Switzerland AG.

Keywords

Primary object segmentation
Salient object detection
Sequential clique optimization
Video object segmentation

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-030-01264-9_32

Cite this

Koh, Y. J., Lee, Y. Y., & Kim, C.-S. (2018). Sequential clique optimization for video object segmentation. In V. Ferrari, C. Sminchisescu, Y. Weiss, & M. Hebert (Eds.), Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings (pp. 537-556). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11218 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-01264-9_32

Sequential clique optimization for video object segmentation. / Koh, Yeong Jun; Lee, Young Yoon; Kim, Chang-Su.
Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. ed. / Vittorio Ferrari; Cristian Sminchisescu; Yair Weiss; Martial Hebert. Springer Verlag, 2018. p. 537-556 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11218 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Koh, YJ, Lee, YY & Kim, C-S 2018, Sequential clique optimization for video object segmentation. in V Ferrari, C Sminchisescu, Y Weiss & M Hebert (eds), Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11218 LNCS, Springer Verlag, pp. 537-556, 15th European Conference on Computer Vision, ECCV 2018, Munich, Germany, 18/9/8. https://doi.org/10.1007/978-3-030-01264-9_32

Koh YJ, Lee YY, Kim CS. Sequential clique optimization for video object segmentation. In Ferrari V, Sminchisescu C, Weiss Y, Hebert M, editors, Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. Springer Verlag. 2018. p. 537-556. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-01264-9_32

Koh, Yeong Jun ; Lee, Young Yoon ; Kim, Chang-Su. / Sequential clique optimization for video object segmentation. Computer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings. editor / Vittorio Ferrari ; Cristian Sminchisescu ; Yair Weiss ; Martial Hebert. Springer Verlag, 2018. pp. 537-556 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Sequential clique optimization for video object segmentation

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