dc.contributor.advisor | Rabiul Alam, Md. Golam | |
dc.contributor.author | Rapheo, Abdullah | |
dc.contributor.author | Billah, A.T.M. Masum | |
dc.contributor.author | Islam, Lamisha | |
dc.contributor.author | MD Yahia Mahim, Abu Shale | |
dc.date.accessioned | 2023-08-13T06:56:06Z | |
dc.date.available | 2023-08-13T06:56:06Z | |
dc.date.copyright | 2023 | |
dc.date.issued | 2023-01 | |
dc.identifier.other | ID: 18101012 | |
dc.identifier.other | ID: 18101008 | |
dc.identifier.other | ID: 18101003 | |
dc.identifier.other | ID: 18101014 | |
dc.identifier.uri | http://hdl.handle.net/10361/19387 | |
dc.description | This 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.description | Cataloged from PDF version of thesis. | |
dc.description | Includes bibliographical references (pages 40-41). | |
dc.description.abstract | 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. | en_US |
dc.description.statementofresponsibility | Abdullah Rapheo | |
dc.description.statementofresponsibility | A.T.M. Masum Billah | |
dc.description.statementofresponsibility | Lamisha Islam | |
dc.description.statementofresponsibility | Abu Shale MD Yahia Mahim | |
dc.format.extent | 41 pages | |
dc.language.iso | en | en_US |
dc.publisher | Brac University | en_US |
dc.rights | 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. | |
dc.subject | Machine learning | en_US |
dc.subject | Eve teasing | en_US |
dc.subject | Detection | en_US |
dc.subject | CNN | en_US |
dc.subject | XGBoost | en_US |
dc.subject | VGG16 | en_US |
dc.subject | Gender classification | en_US |
dc.subject | Posture detection | en_US |
dc.subject.lcsh | Sexual harassment of women--South Asia. | |
dc.title | Eve-teasing detection from video footage using computer vision and artificial intelligence | en_US |
dc.type | Thesis | en_US |
dc.contributor.department | Department of Computer Science and Engineering, Brac University | |
dc.description.degree | B. Computer Science | |