Rushes video summarization by object and event understanding

This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recogn...

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Main Authors: WANG, Feng, NGO, Chong-wah
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2007
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Online Access:https://ink.library.smu.edu.sg/sis_research/6537
https://ink.library.smu.edu.sg/context/sis_research/article/7540/viewcontent/1290031.1290035.pdf
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spelling sg-smu-ink.sis_research-75402022-01-10T03:45:34Z Rushes video summarization by object and event understanding WANG, Feng NGO, Chong-wah This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recognition. Our system is composed of two major steps. First, based on video structuring, we filter undesirable shots and minimize the inter-shot redundancy by repetitive shot detection. Second, a representability measure is proposed to model the presence of objects and four audio-visual events: motion activity of objects, camera motion, scene changes, and speech content, in a video clip. The video clips with the highest representability scores are selected for summarization. The evaluation at TRECVID shows that our experimental results are highly encouraging, where we rank first in EA (easy to understand), second in RE (little redundancy) and third in IN (inclusion of objects and events). 2007-09-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6537 info:doi/10.1145/1290031.1290035 https://ink.library.smu.edu.sg/context/sis_research/article/7540/viewcontent/1290031.1290035.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University event understanding object detection rushes video summarization Artificial Intelligence and Robotics Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic event understanding
object detection
rushes video summarization
Artificial Intelligence and Robotics
Graphics and Human Computer Interfaces
spellingShingle event understanding
object detection
rushes video summarization
Artificial Intelligence and Robotics
Graphics and Human Computer Interfaces
WANG, Feng
NGO, Chong-wah
Rushes video summarization by object and event understanding
description This paper explores a variety of visual and audio analysis techniques in selecting the most representative video clips for rushes summarization at TRECVID 2007. These techniques include object detection, camera motion estimation, keypoint matching and tracking, audio classification and speech recognition. Our system is composed of two major steps. First, based on video structuring, we filter undesirable shots and minimize the inter-shot redundancy by repetitive shot detection. Second, a representability measure is proposed to model the presence of objects and four audio-visual events: motion activity of objects, camera motion, scene changes, and speech content, in a video clip. The video clips with the highest representability scores are selected for summarization. The evaluation at TRECVID shows that our experimental results are highly encouraging, where we rank first in EA (easy to understand), second in RE (little redundancy) and third in IN (inclusion of objects and events).
format text
author WANG, Feng
NGO, Chong-wah
author_facet WANG, Feng
NGO, Chong-wah
author_sort WANG, Feng
title Rushes video summarization by object and event understanding
title_short Rushes video summarization by object and event understanding
title_full Rushes video summarization by object and event understanding
title_fullStr Rushes video summarization by object and event understanding
title_full_unstemmed Rushes video summarization by object and event understanding
title_sort rushes video summarization by object and event understanding
publisher Institutional Knowledge at Singapore Management University
publishDate 2007
url https://ink.library.smu.edu.sg/sis_research/6537
https://ink.library.smu.edu.sg/context/sis_research/article/7540/viewcontent/1290031.1290035.pdf
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