Spatio-temporal image inpainting for video applications

Video inpainting or completion is a vital video improvement technique used to repair or edit digital videos. This paper describes a framework for temporally consistent video completion. The proposed method allows to remove dynamic objects or restore missing or tainted regions presented in a video se...

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Main Authors: Voronin Viacheslav, Marchuk Vladimir, Makov Sergey, Mladenović Vladimir, Cen Yigang
Format: Article
Language:English
Published: Faculty of Technical Sciences in Cacak 2017-01-01
Series:Serbian Journal of Electrical Engineering
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/1451-4869/2017/1451-48691700004V.pdf
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spelling doaj-6f4b72435fa74f5189ca19e7f37fa72d2020-11-25T01:08:02ZengFaculty of Technical Sciences in CacakSerbian Journal of Electrical Engineering1451-48692217-71832017-01-0114222924410.2298/SJEE170116004V1451-48691700004VSpatio-temporal image inpainting for video applicationsVoronin Viacheslav0Marchuk Vladimir1Makov Sergey2Mladenović Vladimir3Cen Yigang4Don State Technical University, Rostov-on-Don, Rostov reg., RussiaDon State Technical University, Rostov-on-Don, Rostov reg., RussiaDon State Technical University, Rostov-on-Don, Rostov reg., RussiaFaculty of Technical Sciences, ČačakBeijing Jiaotong University, Institute of Information Science, Beijing, ChinaVideo inpainting or completion is a vital video improvement technique used to repair or edit digital videos. This paper describes a framework for temporally consistent video completion. The proposed method allows to remove dynamic objects or restore missing or tainted regions presented in a video sequence by utilizing spatial and temporal information from neighboring scenes. Masking algorithm is used for detection of scratches or damaged portions in video frames. The algorithm iteratively performs the following operations: achieve frame; update the scene model; update positions of moving objects; replace parts of the frame occupied by the objects marked for remove by using a background model. In this paper, we extend an image inpainting algorithm based texture and structure reconstruction by incorporating an improved strategy for video. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such as the correct reconstruction of dynamic textures, multiple moving objects and moving background. Experimental comparisons to state-of-the-art video completion methods demonstrate the effectiveness of the proposed approach. It is shown that the proposed spatio-temporal image inpainting method allows restoring a missing blocks and removing a text from the scenes on videos.http://www.doiserbia.nb.rs/img/doi/1451-4869/2017/1451-48691700004V.pdfinpaintingpatchingmaskingspatio-temporalrestoring of missing pixelsvideodynamic textures
collection DOAJ
language English
format Article
sources DOAJ
author Voronin Viacheslav
Marchuk Vladimir
Makov Sergey
Mladenović Vladimir
Cen Yigang
spellingShingle Voronin Viacheslav
Marchuk Vladimir
Makov Sergey
Mladenović Vladimir
Cen Yigang
Spatio-temporal image inpainting for video applications
Serbian Journal of Electrical Engineering
inpainting
patching
masking
spatio-temporal
restoring of missing pixels
video
dynamic textures
author_facet Voronin Viacheslav
Marchuk Vladimir
Makov Sergey
Mladenović Vladimir
Cen Yigang
author_sort Voronin Viacheslav
title Spatio-temporal image inpainting for video applications
title_short Spatio-temporal image inpainting for video applications
title_full Spatio-temporal image inpainting for video applications
title_fullStr Spatio-temporal image inpainting for video applications
title_full_unstemmed Spatio-temporal image inpainting for video applications
title_sort spatio-temporal image inpainting for video applications
publisher Faculty of Technical Sciences in Cacak
series Serbian Journal of Electrical Engineering
issn 1451-4869
2217-7183
publishDate 2017-01-01
description Video inpainting or completion is a vital video improvement technique used to repair or edit digital videos. This paper describes a framework for temporally consistent video completion. The proposed method allows to remove dynamic objects or restore missing or tainted regions presented in a video sequence by utilizing spatial and temporal information from neighboring scenes. Masking algorithm is used for detection of scratches or damaged portions in video frames. The algorithm iteratively performs the following operations: achieve frame; update the scene model; update positions of moving objects; replace parts of the frame occupied by the objects marked for remove by using a background model. In this paper, we extend an image inpainting algorithm based texture and structure reconstruction by incorporating an improved strategy for video. Our algorithm is able to deal with a variety of challenging situations which naturally arise in video inpainting, such as the correct reconstruction of dynamic textures, multiple moving objects and moving background. Experimental comparisons to state-of-the-art video completion methods demonstrate the effectiveness of the proposed approach. It is shown that the proposed spatio-temporal image inpainting method allows restoring a missing blocks and removing a text from the scenes on videos.
topic inpainting
patching
masking
spatio-temporal
restoring of missing pixels
video
dynamic textures
url http://www.doiserbia.nb.rs/img/doi/1451-4869/2017/1451-48691700004V.pdf
work_keys_str_mv AT voroninviacheslav spatiotemporalimageinpaintingforvideoapplications
AT marchukvladimir spatiotemporalimageinpaintingforvideoapplications
AT makovsergey spatiotemporalimageinpaintingforvideoapplications
AT mladenovicvladimir spatiotemporalimageinpaintingforvideoapplications
AT cenyigang spatiotemporalimageinpaintingforvideoapplications
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