Exploiting self-adaptive posture-based focus estimation for lecture video editing

Head pose plays a special role in estimating a presenter’s focuses and actions for lecture video editing. This paper presents an efficient and robust head pose estimation algorithm to cope with the new challenges arising in the content management of lecture videos. These challenges include speed req...

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Main Authors: WANG, Feng, NGO, Chong-wah, PONG, Ting-Chuen
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2005
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Online Access:https://ink.library.smu.edu.sg/sis_research/6375
https://ink.library.smu.edu.sg/context/sis_research/article/7378/viewcontent/MM05.pdf
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Institution: Singapore Management University
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spelling sg-smu-ink.sis_research-73782021-11-23T02:46:08Z Exploiting self-adaptive posture-based focus estimation for lecture video editing WANG, Feng NGO, Chong-wah PONG, Ting-Chuen Head pose plays a special role in estimating a presenter’s focuses and actions for lecture video editing. This paper presents an efficient and robust head pose estimation algorithm to cope with the new challenges arising in the content management of lecture videos. These challenges include speed requirement, low video quality, variant presenting styles and complex settings in modern classrooms. Our algorithm is based on a robust hierarchical representation of skin color clustering and a set of pose templates that are automatically trained. Contextual information is also considered to refine pose estimation. Most importantly, we propose an online learning approach to deal with different presenting styles, which has not been addressed before. We show that the proposed approach can significantly improve the performance of pose estimation. In addition, we also describe how posture is used in focus estimation for lecture video editing by integrating with gesture. 2005-11-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6375 info:doi/10.1145/1101149.1101217 https://ink.library.smu.edu.sg/context/sis_research/article/7378/viewcontent/MM05.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 Lecture Video Pose Estimation Video Editing Computer Sciences 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 Lecture Video
Pose Estimation
Video Editing
Computer Sciences
Graphics and Human Computer Interfaces
spellingShingle Lecture Video
Pose Estimation
Video Editing
Computer Sciences
Graphics and Human Computer Interfaces
WANG, Feng
NGO, Chong-wah
PONG, Ting-Chuen
Exploiting self-adaptive posture-based focus estimation for lecture video editing
description Head pose plays a special role in estimating a presenter’s focuses and actions for lecture video editing. This paper presents an efficient and robust head pose estimation algorithm to cope with the new challenges arising in the content management of lecture videos. These challenges include speed requirement, low video quality, variant presenting styles and complex settings in modern classrooms. Our algorithm is based on a robust hierarchical representation of skin color clustering and a set of pose templates that are automatically trained. Contextual information is also considered to refine pose estimation. Most importantly, we propose an online learning approach to deal with different presenting styles, which has not been addressed before. We show that the proposed approach can significantly improve the performance of pose estimation. In addition, we also describe how posture is used in focus estimation for lecture video editing by integrating with gesture.
format text
author WANG, Feng
NGO, Chong-wah
PONG, Ting-Chuen
author_facet WANG, Feng
NGO, Chong-wah
PONG, Ting-Chuen
author_sort WANG, Feng
title Exploiting self-adaptive posture-based focus estimation for lecture video editing
title_short Exploiting self-adaptive posture-based focus estimation for lecture video editing
title_full Exploiting self-adaptive posture-based focus estimation for lecture video editing
title_fullStr Exploiting self-adaptive posture-based focus estimation for lecture video editing
title_full_unstemmed Exploiting self-adaptive posture-based focus estimation for lecture video editing
title_sort exploiting self-adaptive posture-based focus estimation for lecture video editing
publisher Institutional Knowledge at Singapore Management University
publishDate 2005
url https://ink.library.smu.edu.sg/sis_research/6375
https://ink.library.smu.edu.sg/context/sis_research/article/7378/viewcontent/MM05.pdf
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