Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/161281
Title: A survey on image and video cosegmentation: methods, challenges and analyses
Authors: Ren, Yan
Kong, Adams Wai Kin
Jiao, Licheng
Keywords: Engineering::Computer science and engineering
Issue Date: 2020
Source: Ren, Y., Kong, A. W. K. & Jiao, L. (2020). A survey on image and video cosegmentation: methods, challenges and analyses. Pattern Recognition, 103, 107297-. https://dx.doi.org/10.1016/j.patcog.2020.107297
Project: MOE2016-T2-1-042(S)
Journal: Pattern Recognition
Abstract: Image and video cosegmentation is a newly emerging and rapidly progressing area, which aims at delineating common objects at pixel-level from a group of images or a set of videos. Plenty of related works have been published and implemented in varied applications, but there lacks a systematic survey on both image and video cosegmentation. This paper provides a comprehensive overview including the existing methods, applications, and challenges. Specifically, different cosegmentation problem settings are described, the formulation details of the methods are summarized and their potential applications are listed. Moreover, the benchmark datasets and standard evaluation metrics are also given; and the future directions and unsolved challenges are discussed.
URI: https://hdl.handle.net/10356/161281
ISSN: 0031-3203
DOI: 10.1016/j.patcog.2020.107297
Schools: School of Computer Science and Engineering 
Rights: © 2020 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SCSE Journal Articles

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