Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter

Quality of the intended motions in a video segment is being affected by external perturbations such as hand shakes, or moving platforms where the camera is mounted. This causes the unwanted jitters in a video that becomes additive to the intended motion. This project aims to remove the unwanted moti...

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Main Authors: Magboo, Rhell, Nepomuceno, Johnfel, Rubion, Jericho, Vicente, Patricia
Format: text
Language:English
Published: Animo Repository 2007
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Online Access:https://animorepository.dlsu.edu.ph/etd_bachelors/14314
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Institution: De La Salle University
Language: English
id oai:animorepository.dlsu.edu.ph:etd_bachelors-14956
record_format eprints
spelling oai:animorepository.dlsu.edu.ph:etd_bachelors-149562021-11-17T03:33:00Z Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter Magboo, Rhell Nepomuceno, Johnfel Rubion, Jericho Vicente, Patricia Quality of the intended motions in a video segment is being affected by external perturbations such as hand shakes, or moving platforms where the camera is mounted. This causes the unwanted jitters in a video that becomes additive to the intended motion. This project aims to remove the unwanted motions in a video segment based on a previously developed algorithm following the general stabilization framework. The inter-frame affine parameters that describe the global motion of a video were measured and the cumulative transformation derived from this. Consequently, the intentional motion was estimated using Kalman filter. The difference between the cumulative transformation and the intended motion was taken as the unwanted motion and shall be used in image compensation. The undefined regions that resulted thereafter image compensation were filled using mosaicking. The project was implemented using MATLAB and is presented in a Graphical User Interface (GUI). The performance of the system was evaluated by computing for the Peak Signal-to-Noise Ratio (PSNR) of the output video. Results showed improvements when compared with the original video sequence. The system was also compared to other video stabilization software available in market. 2007-01-01T08:00:00Z text https://animorepository.dlsu.edu.ph/etd_bachelors/14314 Bachelor's Theses English Animo Repository Video tape recorders Kalman filtering--Data processing Engineering
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
language English
topic Video tape recorders
Kalman filtering--Data processing
Engineering
spellingShingle Video tape recorders
Kalman filtering--Data processing
Engineering
Magboo, Rhell
Nepomuceno, Johnfel
Rubion, Jericho
Vicente, Patricia
Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
description Quality of the intended motions in a video segment is being affected by external perturbations such as hand shakes, or moving platforms where the camera is mounted. This causes the unwanted jitters in a video that becomes additive to the intended motion. This project aims to remove the unwanted motions in a video segment based on a previously developed algorithm following the general stabilization framework. The inter-frame affine parameters that describe the global motion of a video were measured and the cumulative transformation derived from this. Consequently, the intentional motion was estimated using Kalman filter. The difference between the cumulative transformation and the intended motion was taken as the unwanted motion and shall be used in image compensation. The undefined regions that resulted thereafter image compensation were filled using mosaicking. The project was implemented using MATLAB and is presented in a Graphical User Interface (GUI). The performance of the system was evaluated by computing for the Peak Signal-to-Noise Ratio (PSNR) of the output video. Results showed improvements when compared with the original video sequence. The system was also compared to other video stabilization software available in market.
format text
author Magboo, Rhell
Nepomuceno, Johnfel
Rubion, Jericho
Vicente, Patricia
author_facet Magboo, Rhell
Nepomuceno, Johnfel
Rubion, Jericho
Vicente, Patricia
author_sort Magboo, Rhell
title Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
title_short Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
title_full Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
title_fullStr Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
title_full_unstemmed Windows-based implementation of probabilistic video stabilization and compensation algorithm using Kalman Filter
title_sort windows-based implementation of probabilistic video stabilization and compensation algorithm using kalman filter
publisher Animo Repository
publishDate 2007
url https://animorepository.dlsu.edu.ph/etd_bachelors/14314
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