Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis
Understanding and analysing video data from static or mobile surveillance cameras often requires knowledge of the scene and the camera placement. In this article, we provide a way to simplify the user's task of understanding the scene by rendering the camera view as if observed from the user...
Main Authors: | , , , , |
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Format: | Journal article |
Language: | English |
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2011
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_version_ | 1797072441740099584 |
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author | Mei, C Sommerlade, E Sibley, G Newman, P Reid, I |
author_facet | Mei, C Sommerlade, E Sibley, G Newman, P Reid, I |
author_sort | Mei, C |
collection | OXFORD |
description | Understanding and analysing video data from static or mobile surveillance cameras often requires knowledge of the scene and the camera placement. In this article, we provide a way to simplify the user's task of understanding the scene by rendering the camera view as if observed from the user's perspective by estimating his position using a real-time visual SLAM system. Augmenting the view is referred to as hidden view synthesis. Compared to previous work, the current approach improves by simplifying the setup and requiring minimal user input. This is achieved by building a map of the environment using a visual SLAM system and then registering the surveillance camera in this map. By exploiting the map, a different moving camera can render hidden views in realtime at 30Hz. We discuss some of the challenges remaining for full automation. Results are shown in an indoor environment for surveillance applications and outdoors with application to improved safety in transport. © 2011 IEEE. |
first_indexed | 2024-03-06T23:07:42Z |
format | Journal article |
id | oxford-uuid:646a5f4b-2733-4c71-9258-1aaee4e4b5ba |
institution | University of Oxford |
language | English |
last_indexed | 2024-03-06T23:07:42Z |
publishDate | 2011 |
record_format | dspace |
spelling | oxford-uuid:646a5f4b-2733-4c71-9258-1aaee4e4b5ba2022-03-26T18:18:44ZHidden view synthesis using real-time visual SLAM for simplifying video surveillance analysisJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:646a5f4b-2733-4c71-9258-1aaee4e4b5baEnglishSymplectic Elements at Oxford2011Mei, CSommerlade, ESibley, GNewman, PReid, IUnderstanding and analysing video data from static or mobile surveillance cameras often requires knowledge of the scene and the camera placement. In this article, we provide a way to simplify the user's task of understanding the scene by rendering the camera view as if observed from the user's perspective by estimating his position using a real-time visual SLAM system. Augmenting the view is referred to as hidden view synthesis. Compared to previous work, the current approach improves by simplifying the setup and requiring minimal user input. This is achieved by building a map of the environment using a visual SLAM system and then registering the surveillance camera in this map. By exploiting the map, a different moving camera can render hidden views in realtime at 30Hz. We discuss some of the challenges remaining for full automation. Results are shown in an indoor environment for surveillance applications and outdoors with application to improved safety in transport. © 2011 IEEE. |
spellingShingle | Mei, C Sommerlade, E Sibley, G Newman, P Reid, I Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title | Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title_full | Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title_fullStr | Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title_full_unstemmed | Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title_short | Hidden view synthesis using real-time visual SLAM for simplifying video surveillance analysis |
title_sort | hidden view synthesis using real time visual slam for simplifying video surveillance analysis |
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