Sequential clique optimization for video object segmentation

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

    Research output: Chapter in Book/Report/Conference proceedingConference 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 languageEnglish
    Title of host publicationComputer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
    EditorsVittorio Ferrari, Cristian Sminchisescu, Yair Weiss, Martial Hebert
    PublisherSpringer Verlag
    Pages537-556
    Number of pages20
    ISBN (Print)9783030012632
    DOIs
    Publication statusPublished - 2018
    Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
    Duration: 2018 Sept 82018 Sept 14

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11218 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Other

    Other15th European Conference on Computer Vision, ECCV 2018
    Country/TerritoryGermany
    CityMunich
    Period18/9/818/9/14

    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

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