Eve teasing, a form of public harassment and assault
on women, is a significant issue that causes severe distress,
particularly among young women and girls. The rising incidence
of eve teasing in Bangladesh has led to severe crimes such as
rape and murder, with many offenders escaping due to a lack of
evidence and effective monitoring. This paper presents a novel
approach using computer vision and machine learning methods
to detect eve teasing from video material in various situations.
Our proposed solution combines gender detection, expression
analysis, and gesture recognition to identify behaviors indicative
of eve teasing. The system integrates male-female identification,
human behavior detection, and CCTV-based monitoring or video
footage analysis to identify such critical incidents. Additionally,
the approach includes determining the participants involved in
the scenario to provide comprehensive evidence of harassment.
By enabling more accurate detection and verification of eve
teasing in real time, our method offers a promising tool to
help victims prove harassment and support law enforcement in
apprehending offenders, thereby contributing to a safer public
environment.