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Occlusion handling for augmented reality environment using neural network image segmentation: A review.

Recently, the advancements of handling occlusions for Augmented Reality (AR) introduces neural network-based image segmentation methods. However, it comes with increased computational costs. There has been some research that try to tackle this issue. Therefore, this paper compiles and reviews the re...

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Main Authors: Ahmad, Muhammad Anwar, Mohd. Suaib, Norhaida, Ismail, Ajune Wanis
Format: Conference or Workshop Item
Published: 2022
Subjects:
T58.5-58.64 Information technology
Online Access:http://eprints.utm.my/108794/
http://dx.doi.org/10.1063/5.0198741
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id my.utm.108794
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spelling my.utm.1087942024-12-09T06:23:17Z http://eprints.utm.my/108794/ Occlusion handling for augmented reality environment using neural network image segmentation: A review. Ahmad, Muhammad Anwar Mohd. Suaib, Norhaida Ismail, Ajune Wanis T58.5-58.64 Information technology Recently, the advancements of handling occlusions for Augmented Reality (AR) introduces neural network-based image segmentation methods. However, it comes with increased computational costs. There has been some research that try to tackle this issue. Therefore, this paper compiles and reviews the recent articles that covers on this topic in order to identify the current achievements and the future works. The structure of this paper consists of explaining the basics of neural network-based image segmentation, discussing the methods in the published articles and suggesting expected future improvements. 14 articles were identified and 6 of them are discussed in this article. From the discussions, it is found that the common image segmentation methods comprise of semantic and instance segmentation, with instance segmentation giving more accurate and robust results for tracking objects but with higher computational costs. Some methods also incorporate depth-based techniques and 3D reconstruction to improve the accuracy. Based on the advancements, it is concluded that future works on this topic will be more on improving instance segmentation methods in order to reduce the computational costs. 2022-06-07 Conference or Workshop Item PeerReviewed Ahmad, Muhammad Anwar and Mohd. Suaib, Norhaida and Ismail, Ajune Wanis (2022) Occlusion handling for augmented reality environment using neural network image segmentation: A review. In: 4th International Conference on Green Engineering and Technology 2022, IConGETech 2022, 17 November 2022 - 18 November 2022, Seoul, South Korea. http://dx.doi.org/10.1063/5.0198741
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T58.5-58.64 Information technology
spellingShingle T58.5-58.64 Information technology
Ahmad, Muhammad Anwar
Mohd. Suaib, Norhaida
Ismail, Ajune Wanis
Occlusion handling for augmented reality environment using neural network image segmentation: A review.
description Recently, the advancements of handling occlusions for Augmented Reality (AR) introduces neural network-based image segmentation methods. However, it comes with increased computational costs. There has been some research that try to tackle this issue. Therefore, this paper compiles and reviews the recent articles that covers on this topic in order to identify the current achievements and the future works. The structure of this paper consists of explaining the basics of neural network-based image segmentation, discussing the methods in the published articles and suggesting expected future improvements. 14 articles were identified and 6 of them are discussed in this article. From the discussions, it is found that the common image segmentation methods comprise of semantic and instance segmentation, with instance segmentation giving more accurate and robust results for tracking objects but with higher computational costs. Some methods also incorporate depth-based techniques and 3D reconstruction to improve the accuracy. Based on the advancements, it is concluded that future works on this topic will be more on improving instance segmentation methods in order to reduce the computational costs.
format Conference or Workshop Item
author Ahmad, Muhammad Anwar
Mohd. Suaib, Norhaida
Ismail, Ajune Wanis
author_facet Ahmad, Muhammad Anwar
Mohd. Suaib, Norhaida
Ismail, Ajune Wanis
author_sort Ahmad, Muhammad Anwar
title Occlusion handling for augmented reality environment using neural network image segmentation: A review.
title_short Occlusion handling for augmented reality environment using neural network image segmentation: A review.
title_full Occlusion handling for augmented reality environment using neural network image segmentation: A review.
title_fullStr Occlusion handling for augmented reality environment using neural network image segmentation: A review.
title_full_unstemmed Occlusion handling for augmented reality environment using neural network image segmentation: A review.
title_sort occlusion handling for augmented reality environment using neural network image segmentation: a review.
publishDate 2022
url http://eprints.utm.my/108794/
http://dx.doi.org/10.1063/5.0198741
_version_ 1818834049932722176
score 13.223943

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