The augmented human - visual movement magnification

The world is filled with visually subtle signals that are important such as a person’s pulse, blood flow in a person’s face, and the gentle swaying of a towering crane, yet it is an inevitable fact that the human perception is very limited to be able to see the visual patterns. The use of optical mi...

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Main Author: Siti Nazhura Muhamad Anuar
Other Authors: Cham Tat Jen
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157456
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1574562022-05-21T07:22:18Z The augmented human - visual movement magnification Siti Nazhura Muhamad Anuar Cham Tat Jen School of Computer Science and Engineering ASTJCham@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision The world is filled with visually subtle signals that are important such as a person’s pulse, blood flow in a person’s face, and the gentle swaying of a towering crane, yet it is an inevitable fact that the human perception is very limited to be able to see the visual patterns. The use of optical microscopes can easily identify the differences that are present in objects. To amplify subtle motion and colour changes in videos, this study explores the Eulerian Video Magnification (EVM) as a computational workaround for optical microscopes. The EVM process is an image processing technique that magnifies subtle, microscopic amounts of motion and colour variations in a video sequence which are not visible to the naked eyes. It is accomplished by applying a spatial filter to the video sequence as the initial step, followed by applying a temporal bandpass filter to isolate the relevant frequencies, and lastly magnifying the frequencies and combining them to the original video. Applying EVM onto videos will exponentially magnify any subtle movements or amplify significant colour changes as though as the variations are viewed from an optical microscope. A common example of utilizing EVM is extracting the magnified motions to reveal respiratory activities from a video of an inhalation process that is difficult for the human eye to detect due to the low spatial capability. Therefore, the use of EVM can provide ceaseless possibilities in various research areas that require subtle motions or colour variations to be viewed from a computational microscope. Bachelor of Engineering (Computer Engineering) 2022-05-21T07:22:18Z 2022-05-21T07:22:18Z 2022 Final Year Project (FYP) Siti Nazhura Muhamad Anuar (2022). The augmented human - visual movement magnification. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157456 https://hdl.handle.net/10356/157456 en SCSE21-0258 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Siti Nazhura Muhamad Anuar
The augmented human - visual movement magnification
description The world is filled with visually subtle signals that are important such as a person’s pulse, blood flow in a person’s face, and the gentle swaying of a towering crane, yet it is an inevitable fact that the human perception is very limited to be able to see the visual patterns. The use of optical microscopes can easily identify the differences that are present in objects. To amplify subtle motion and colour changes in videos, this study explores the Eulerian Video Magnification (EVM) as a computational workaround for optical microscopes. The EVM process is an image processing technique that magnifies subtle, microscopic amounts of motion and colour variations in a video sequence which are not visible to the naked eyes. It is accomplished by applying a spatial filter to the video sequence as the initial step, followed by applying a temporal bandpass filter to isolate the relevant frequencies, and lastly magnifying the frequencies and combining them to the original video. Applying EVM onto videos will exponentially magnify any subtle movements or amplify significant colour changes as though as the variations are viewed from an optical microscope. A common example of utilizing EVM is extracting the magnified motions to reveal respiratory activities from a video of an inhalation process that is difficult for the human eye to detect due to the low spatial capability. Therefore, the use of EVM can provide ceaseless possibilities in various research areas that require subtle motions or colour variations to be viewed from a computational microscope.
author2 Cham Tat Jen
author_facet Cham Tat Jen
Siti Nazhura Muhamad Anuar
format Final Year Project
author Siti Nazhura Muhamad Anuar
author_sort Siti Nazhura Muhamad Anuar
title The augmented human - visual movement magnification
title_short The augmented human - visual movement magnification
title_full The augmented human - visual movement magnification
title_fullStr The augmented human - visual movement magnification
title_full_unstemmed The augmented human - visual movement magnification
title_sort augmented human - visual movement magnification
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157456
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