Eve-teasing detection from video footage using computer vision and artificial intelligence

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

Bibliographic Details
Main Authors:	Rapheo, Abdullah, Billah, A.T.M. Masum, Islam, Lamisha, MD Yahia Mahim, Abu Shale
Other Authors:	Rabiul Alam, Md. Golam
Format:	Thesis
Language:	English
Published:	Brac University 2023
Subjects:	Machine learning Eve teasing Detection CNN XGBoost VGG16 Gender classification Posture detection Sexual harassment of women > South Asia.
Online Access:	http://hdl.handle.net/10361/19387

id	10361-19387
record_format	dspace
spelling	10361-193872023-08-13T21:02:08Z Eve-teasing detection from video footage using computer vision and artificial intelligence Rapheo, Abdullah Billah, A.T.M. Masum Islam, Lamisha MD Yahia Mahim, Abu Shale Rabiul Alam, Md. Golam Department of Computer Science and Engineering, Brac University Machine learning Eve teasing Detection CNN XGBoost VGG16 Gender classification Posture detection Sexual harassment of women--South Asia. This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023. Cataloged from PDF version of thesis. Includes bibliographical references (pages 40-41). We present computer vision approaches combined with machine learning techniques to detect eve-teasing from any video material, which may be used in any situa tion. Eve teasing is a colloquial term for public sexual harassment or sexual assault committed primarily against women by men. Eve-teasing is a common and pro foundly distressing reality for young women, particularly young girls. Moreover, in Bangladesh, the number of reported occurrences of Eve-Teasing is increasing at an alarming rate. Already eve-teasing is leading to rape and then murder. Due to a lack of proof and adequate supervision, the vast majority of criminals can get away with their crimes. In order to eliminate this problem, we suggested computer vi sion approaches for detecting eve-teasing in any video clip, which may be used in any critical situation. Our proposed method uses machine learning and computer vision to detect human Gender, expression, posture, and gesture and combine them to verify a matching human behavior in a critical situation to justify. When em ploying the combination of male-female identification, human behavior detection, and CCTV-based monitoring systems or video footage, the system can identify such vital conditions in our suggested method. Also included is the ability to determine who is participating and who is not in the scenario. Women who want to prove eve-teasing or harassment may find the procedures proposed helpful while ensuring the actual offender is punished. Abdullah Rapheo A.T.M. Masum Billah Lamisha Islam Abu Shale MD Yahia Mahim B. Computer Science 2023-08-13T06:56:06Z 2023-08-13T06:56:06Z 2023 2023-01 Thesis ID: 18101012 ID: 18101008 ID: 18101003 ID: 18101014 http://hdl.handle.net/10361/19387 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. 41 pages application/pdf Brac University
institution	Brac University
collection	Institutional Repository
language	English
topic	Machine learning Eve teasing Detection CNN XGBoost VGG16 Gender classification Posture detection Sexual harassment of women--South Asia.
spellingShingle	Machine learning Eve teasing Detection CNN XGBoost VGG16 Gender classification Posture detection Sexual harassment of women--South Asia. Rapheo, Abdullah Billah, A.T.M. Masum Islam, Lamisha MD Yahia Mahim, Abu Shale Eve-teasing detection from video footage using computer vision and artificial intelligence
description	This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.
author2	Rabiul Alam, Md. Golam
author_facet	Rabiul Alam, Md. Golam Rapheo, Abdullah Billah, A.T.M. Masum Islam, Lamisha MD Yahia Mahim, Abu Shale
format	Thesis
author	Rapheo, Abdullah Billah, A.T.M. Masum Islam, Lamisha MD Yahia Mahim, Abu Shale
author_sort	Rapheo, Abdullah
title	Eve-teasing detection from video footage using computer vision and artificial intelligence
title_short	Eve-teasing detection from video footage using computer vision and artificial intelligence
title_full	Eve-teasing detection from video footage using computer vision and artificial intelligence
title_fullStr	Eve-teasing detection from video footage using computer vision and artificial intelligence
title_full_unstemmed	Eve-teasing detection from video footage using computer vision and artificial intelligence
title_sort	eve-teasing detection from video footage using computer vision and artificial intelligence
publisher	Brac University
publishDate	2023
url	http://hdl.handle.net/10361/19387
work_keys_str_mv	AT rapheoabdullah eveteasingdetectionfromvideofootageusingcomputervisionandartificialintelligence AT billahatmmasum eveteasingdetectionfromvideofootageusingcomputervisionandartificialintelligence AT islamlamisha eveteasingdetectionfromvideofootageusingcomputervisionandartificialintelligence AT mdyahiamahimabushale eveteasingdetectionfromvideofootageusingcomputervisionandartificialintelligence
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Eve-teasing detection from video footage using computer vision and artificial intelligence

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