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A Survey on Salient Object Detection

T. Hemanth Kumar1 , P. Chandra Sekhar Reddy2

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 991-994, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.991994

Online published on Apr 30, 2019

Copyright © T. Hemanth Kumar, P. Chandra Sekhar Reddy . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: T. Hemanth Kumar, P. Chandra Sekhar Reddy, “A Survey on Salient Object Detection,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.991-994, 2019.

MLA Style Citation: T. Hemanth Kumar, P. Chandra Sekhar Reddy "A Survey on Salient Object Detection." International Journal of Computer Sciences and Engineering 7.4 (2019): 991-994.

APA Style Citation: T. Hemanth Kumar, P. Chandra Sekhar Reddy, (2019). A Survey on Salient Object Detection. International Journal of Computer Sciences and Engineering, 7(4), 991-994.

BibTex Style Citation:
@article{Kumar_2019,
author = {T. Hemanth Kumar, P. Chandra Sekhar Reddy},
title = {A Survey on Salient Object Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {991-994},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4155},
doi = {https://doi.org/10.26438/ijcse/v7i4.991994}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.991994}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4155
TI - A Survey on Salient Object Detection
T2 - International Journal of Computer Sciences and Engineering
AU - T. Hemanth Kumar, P. Chandra Sekhar Reddy
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 991-994
IS - 4
VL - 7
SN - 2347-2693
ER -

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Abstract

Distinguishing and segmenting salient objects in like manner scenes, every now and again implied as salient object detection, has pulled in a huge amount of eagerness for PC vision. While various models have been proposed and a couple of utilizations have risen, yet a profound comprehensionof issues is insufficient. We hope to give a broad study of progressing in salient object identification and mastermind this area among other immovably related domains, for instance, regular picture segmentation, object recommendation age, and saliency for obsession forecast. Covering 228 distributions, we review i. Roots, key ideas, and assignments, ii.Center methods and principle displaying patterns, and iii.Datasets and assessment measurements in salient object identification. We likewise talk about open issues, for example, assessment measurements and dataset predisposition in model execution and propose future research bearings.

Key-Words / Index Term

Video-saliency, Spatio-temporal constraints, Reliableregions, global saliencyoptimization

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