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dc.contributor.advisorRabiul Alam, Md. Golam
dc.contributor.authorRapheo, Abdullah
dc.contributor.authorBillah, A.T.M. Masum
dc.contributor.authorIslam, Lamisha
dc.contributor.authorMD Yahia Mahim, Abu Shale
dc.date.accessioned2023-08-13T06:56:06Z
dc.date.available2023-08-13T06:56:06Z
dc.date.copyright2023
dc.date.issued2023-01
dc.identifier.otherID: 18101012
dc.identifier.otherID: 18101008
dc.identifier.otherID: 18101003
dc.identifier.otherID: 18101014
dc.identifier.urihttp://hdl.handle.net/10361/19387
dc.descriptionThis thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2023.en_US
dc.descriptionCataloged from PDF version of thesis.
dc.descriptionIncludes bibliographical references (pages 40-41).
dc.description.abstractWe 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.en_US
dc.description.statementofresponsibilityAbdullah Rapheo
dc.description.statementofresponsibilityA.T.M. Masum Billah
dc.description.statementofresponsibilityLamisha Islam
dc.description.statementofresponsibilityAbu Shale MD Yahia Mahim
dc.format.extent41 pages
dc.language.isoenen_US
dc.publisherBrac Universityen_US
dc.rightsBrac 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.
dc.subjectMachine learningen_US
dc.subjectEve teasingen_US
dc.subjectDetectionen_US
dc.subjectCNNen_US
dc.subjectXGBoosten_US
dc.subjectVGG16en_US
dc.subjectGender classificationen_US
dc.subjectPosture detectionen_US
dc.subject.lcshSexual harassment of women--South Asia.
dc.titleEve-teasing detection from video footage using computer vision and artificial intelligenceen_US
dc.typeThesisen_US
dc.contributor.departmentDepartment of Computer Science and Engineering, Brac University
dc.description.degreeB. Computer Science


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