The augmented human - visual movement magnification

Over the years of mankind’s history, the advent of tools has allowed us to extend our human capabilities. Each of the 5 senses (Touch, Hearing, Smell, Taste, and most importantly Sight) have received countless enhancements through the power of human ingenuity and creativity, borrowing elements from...

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Main Author: Tan, Ryan Jinn-En
Other Authors: Cham Tat Jen
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2023
Subjects:
Online Access:https://hdl.handle.net/10356/166679
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1666792023-05-12T15:36:28Z The augmented human - visual movement magnification Tan, Ryan Jinn-En 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 Over the years of mankind’s history, the advent of tools has allowed us to extend our human capabilities. Each of the 5 senses (Touch, Hearing, Smell, Taste, and most importantly Sight) have received countless enhancements through the power of human ingenuity and creativity, borrowing elements from nature, science and sometimes our imagination granting us the ability to achieve feats that continue to scale in both scope and aspirations. This report discusses utilising an existing Learning-based Video Motion Magnification (LVMM) that allows users to observe previously indiscernible movement such as breathing, pulse and tiny facial movements of other people from a video recorded using conventional camera equipment (such as a mobile phone), before feeding the output data into a separate deep-learning image classification model built using Keras to train it into discerning between a person inhaling and exhaling. The image classification software will serve as a foundation for monitoring a person’s respiratory cycle and potentially be used in conjunction with existing medical devices to further expand the groundwork for non-invasive patient care. Bachelor of Engineering (Computer Science) 2023-05-08T04:39:02Z 2023-05-08T04:39:02Z 2023 Final Year Project (FYP) Tan, R. J. (2023). The augmented human - visual movement magnification. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/166679 https://hdl.handle.net/10356/166679 en SCSE22-0284 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
Tan, Ryan Jinn-En
The augmented human - visual movement magnification
description Over the years of mankind’s history, the advent of tools has allowed us to extend our human capabilities. Each of the 5 senses (Touch, Hearing, Smell, Taste, and most importantly Sight) have received countless enhancements through the power of human ingenuity and creativity, borrowing elements from nature, science and sometimes our imagination granting us the ability to achieve feats that continue to scale in both scope and aspirations. This report discusses utilising an existing Learning-based Video Motion Magnification (LVMM) that allows users to observe previously indiscernible movement such as breathing, pulse and tiny facial movements of other people from a video recorded using conventional camera equipment (such as a mobile phone), before feeding the output data into a separate deep-learning image classification model built using Keras to train it into discerning between a person inhaling and exhaling. The image classification software will serve as a foundation for monitoring a person’s respiratory cycle and potentially be used in conjunction with existing medical devices to further expand the groundwork for non-invasive patient care.
author2 Cham Tat Jen
author_facet Cham Tat Jen
Tan, Ryan Jinn-En
format Final Year Project
author Tan, Ryan Jinn-En
author_sort Tan, Ryan Jinn-En
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 2023
url https://hdl.handle.net/10356/166679
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