Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection

This study explores the feasibility of using low-resolution cameras as a means of detecting facial movements for lie detection. Micro-expressions, however, are difficult to detect by the human eye due to their short duration and low intensity, thus the research explores the possibility of extracting...

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Main Authors: Lim,, Lanz Kendall, Ong, Eden Paige, Ramos, Carl Arjan, Dellosa, Mico, Flores, Fritz Kevin
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Published: Animo Repository 2021
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Online Access:https://animorepository.dlsu.edu.ph/conf_shsrescon/2021/paper_csr/2
https://animorepository.dlsu.edu.ph/context/conf_shsrescon/article/1658/viewcontent/CSTR_Feasibility_of_Using_Phone_and_Web_Cameras.pdf
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Institution: De La Salle University
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spelling oai:animorepository.dlsu.edu.ph:conf_shsrescon-16582023-08-23T10:07:15Z Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection Lim,, Lanz Kendall Ong, Eden Paige Ramos, Carl Arjan Dellosa, Mico Flores, Fritz Kevin This study explores the feasibility of using low-resolution cameras as a means of detecting facial movements for lie detection. Micro-expressions, however, are difficult to detect by the human eye due to their short duration and low intensity, thus the research explores the possibility of extracting micro-expressions from phone or web cameras that have low resolution and framerate. The collected videos are the processed using time series processing, to obtain both facial data points extracted from facial landmark detection models, as well as image generation from the obtained datapoints to produce a face structure. The classification mainly focuses on the use of common machine learning algorithms, to detect facial movement patterns, in the hopes of classifying people telling truths or lies. The tests ultimately proved to have a low accuracy in classification, but the results show that the methodology may contribute to other domains, such as in person identification, as well as possible recommendations for future works. 2021-04-29T20:00:00Z text application/pdf https://animorepository.dlsu.edu.ph/conf_shsrescon/2021/paper_csr/2 https://animorepository.dlsu.edu.ph/context/conf_shsrescon/article/1658/viewcontent/CSTR_Feasibility_of_Using_Phone_and_Web_Cameras.pdf DLSU Senior High School Research Congress Animo Repository Facial Landmarks, Image Transform, Machine Learning, Time Series.
institution De La Salle University
building De La Salle University Library
continent Asia
country Philippines
Philippines
content_provider De La Salle University Library
collection DLSU Institutional Repository
topic Facial Landmarks, Image Transform, Machine Learning, Time Series.
spellingShingle Facial Landmarks, Image Transform, Machine Learning, Time Series.
Lim,, Lanz Kendall
Ong, Eden Paige
Ramos, Carl Arjan
Dellosa, Mico
Flores, Fritz Kevin
Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
description This study explores the feasibility of using low-resolution cameras as a means of detecting facial movements for lie detection. Micro-expressions, however, are difficult to detect by the human eye due to their short duration and low intensity, thus the research explores the possibility of extracting micro-expressions from phone or web cameras that have low resolution and framerate. The collected videos are the processed using time series processing, to obtain both facial data points extracted from facial landmark detection models, as well as image generation from the obtained datapoints to produce a face structure. The classification mainly focuses on the use of common machine learning algorithms, to detect facial movement patterns, in the hopes of classifying people telling truths or lies. The tests ultimately proved to have a low accuracy in classification, but the results show that the methodology may contribute to other domains, such as in person identification, as well as possible recommendations for future works.
format text
author Lim,, Lanz Kendall
Ong, Eden Paige
Ramos, Carl Arjan
Dellosa, Mico
Flores, Fritz Kevin
author_facet Lim,, Lanz Kendall
Ong, Eden Paige
Ramos, Carl Arjan
Dellosa, Mico
Flores, Fritz Kevin
author_sort Lim,, Lanz Kendall
title Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
title_short Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
title_full Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
title_fullStr Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
title_full_unstemmed Feasibility of Using Phone and Web Cameras to Detect Micro-Expressions for Lie Detection
title_sort feasibility of using phone and web cameras to detect micro-expressions for lie detection
publisher Animo Repository
publishDate 2021
url https://animorepository.dlsu.edu.ph/conf_shsrescon/2021/paper_csr/2
https://animorepository.dlsu.edu.ph/context/conf_shsrescon/article/1658/viewcontent/CSTR_Feasibility_of_Using_Phone_and_Web_Cameras.pdf
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