Determining motion saliency in videos

This Final Year Project describes an algorithm for obtaining and extracting information that attracts user attention in a video clip. The key factors that make a region attractive are the motion that happened in a video, the low-level features like image orientation and intensity and also the semant...

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Main Author: Tan, Angeline Chern Kai.
Other Authors: Deepu Rajan
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/39959
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-399592023-03-03T20:44:00Z Determining motion saliency in videos Tan, Angeline Chern Kai. Deepu Rajan School of Computer Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision This Final Year Project describes an algorithm for obtaining and extracting information that attracts user attention in a video clip. The key factors that make a region attractive are the motion that happened in a video, the low-level features like image orientation and intensity and also the semantic influence in a video. The exploration of the project is supported by research and study on several related works. The function of analyzing the related work is to aid in the project planning cycle. With this workflow, it will be able to help in project designing and also prepare for project implementation. The purpose of this project is to create an algorithm that identifies the attention attracting regions and generate a skimmed version which refers to a concise representation of the original video clip. The region of attractions in a video clip in this project is identified by motion. The motion saliency information is generated based on motion vector information with spatial and temporal coherency. During the process, experimental results were obtained and evaluated to justify this accuracy. The final results of the skimmed video were produced and it showed excellent results. Bachelor of Engineering (Computer Engineering) 2010-06-08T06:39:38Z 2010-06-08T06:39:38Z 2010 2010 Final Year Project (FYP) http://hdl.handle.net/10356/39959 en Nanyang Technological University 120 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Tan, Angeline Chern Kai.
Determining motion saliency in videos
description This Final Year Project describes an algorithm for obtaining and extracting information that attracts user attention in a video clip. The key factors that make a region attractive are the motion that happened in a video, the low-level features like image orientation and intensity and also the semantic influence in a video. The exploration of the project is supported by research and study on several related works. The function of analyzing the related work is to aid in the project planning cycle. With this workflow, it will be able to help in project designing and also prepare for project implementation. The purpose of this project is to create an algorithm that identifies the attention attracting regions and generate a skimmed version which refers to a concise representation of the original video clip. The region of attractions in a video clip in this project is identified by motion. The motion saliency information is generated based on motion vector information with spatial and temporal coherency. During the process, experimental results were obtained and evaluated to justify this accuracy. The final results of the skimmed video were produced and it showed excellent results.
author2 Deepu Rajan
author_facet Deepu Rajan
Tan, Angeline Chern Kai.
format Final Year Project
author Tan, Angeline Chern Kai.
author_sort Tan, Angeline Chern Kai.
title Determining motion saliency in videos
title_short Determining motion saliency in videos
title_full Determining motion saliency in videos
title_fullStr Determining motion saliency in videos
title_full_unstemmed Determining motion saliency in videos
title_sort determining motion saliency in videos
publishDate 2010
url http://hdl.handle.net/10356/39959
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