MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network

This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Araf, Tashreef Abdullah
Άλλοι συγγραφείς: Alam, Golam Rabiul
Μορφή: Thesis
Γλώσσα:English
Έκδοση: Brac University 2024
Θέματα:
Διαθέσιμο Online:http://hdl.handle.net/10361/23081
id 10361-23081
record_format dspace
spelling 10361-230812024-06-03T21:01:24Z MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network Araf, Tashreef Abdullah Alam, Golam Rabiul Department of Computer Science and Engineering, Brac University VisageEmotioNet Facial expression Micro-facial expression Pixel binning Facial expression Neural networks (Computer science) This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis Includes bibliographical references (pages 42-46). Facial-Expression recognition is a very intriguing field of research, due to the complexity in its approach and applicability of widely available databases. However, Micro-expression recognition is quite a vague yet growing area of research due to its applicability in revealing minute facial expressions. These emotional triggers happen only under very pressing circumstances, which means detecting them can also be extremely tough due to shortage of time during which it lasts. In this study, the approach to Micro-facial expression detection is to explore passive and real-time observation that produces a great result for micro-facial expression recognition using a vast data set trained using new training techniques. A total of 59 papers were analyzed whose concepts were associative to our main thesis concept, which were categorized into three stages: Construction of a new dataset which constituted of standard and new facial images, which was trained using innovative image processing pipelines, implementation of a new Binary Pattern layer our Neural Network layer to accelerate the models expression tracking abilities, creation of a new facial model capable of facial and micro-facial expression recognition that performs better statistically when compared to its counterparts. Furthermore, the new model was tested in both artificial and real-world scenarios to accentuate the reliability of the data sources. Tashreef Abdullah Araf M.Sc. in Computer Science 2024-06-03T05:39:51Z 2024-06-03T05:39:51Z ©2023 2023-09 Thesis ID 21366023 http://hdl.handle.net/10361/23081 en Brac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 58 pages application/pdf Brac University
institution Brac University
collection Institutional Repository
language English
topic VisageEmotioNet
Facial expression
Micro-facial expression
Pixel binning
Facial expression
Neural networks (Computer science)
spellingShingle VisageEmotioNet
Facial expression
Micro-facial expression
Pixel binning
Facial expression
Neural networks (Computer science)
Araf, Tashreef Abdullah
MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
description This thesis is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2023.
author2 Alam, Golam Rabiul
author_facet Alam, Golam Rabiul
Araf, Tashreef Abdullah
format Thesis
author Araf, Tashreef Abdullah
author_sort Araf, Tashreef Abdullah
title MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
title_short MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
title_full MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
title_fullStr MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
title_full_unstemmed MEDNET – an approach to facial micro-emotion recognition using pixel binning and local Binary pattern - convolutional neural network
title_sort mednet – an approach to facial micro-emotion recognition using pixel binning and local binary pattern - convolutional neural network
publisher Brac University
publishDate 2024
url http://hdl.handle.net/10361/23081
work_keys_str_mv AT araftashreefabdullah mednetanapproachtofacialmicroemotionrecognitionusingpixelbinningandlocalbinarypatternconvolutionalneuralnetwork
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