Abstract
The illegal disposal of trash is a major public health and environmental concern. Disposing of trash in unplanned places poses serious health and environmental risks. We should try to restrict public trash cans as much as possible. This research focuses on automating the penalization of litterbugs, addressing the persistent problem of littering in public places. Traditional approaches relying on manual intervention and witness reporting suffer from delays, inaccuracies, and anonymity issues. To overcome these challenges, this paper proposes a fully automated system that utilizes surveillance cameras and advanced computer vision algorithms for litter detection, object tracking, and face recognition. The system accurately identifies and tracks individuals engaged in littering activities, attaches their identities through face recognition, and enables efficient enforcement of anti-littering policies. By reducing reliance on manual intervention, minimizing human error, and providing prompt identification, the proposed system offers significant advantages in addressing littering incidents. The primary contribution of this research lies in the implementation of the proposed system, leveraging advanced technologies to enhance surveillance operations and automate the penalization of litterbugs.
Abstract (translated)
垃圾随意丢弃是一个重大的公共卫生和环境问题。在未经规划的地方丢弃垃圾会带来严重的健康和环境风险。我们应该尽可能地限制公共场所的垃圾桶。这项研究专注于自动惩处乱扔垃圾者，解决公共场所乱扔垃圾的长期问题。传统方法依赖于人工干预和目击报告，存在延迟、不准确和匿名性问题。为了克服这些挑战，本文提出了一个完全自动化的系统，利用摄像头和先进的计算机视觉算法进行垃圾检测、物体追踪和面部识别。该系统准确识别和跟踪进行乱扔垃圾活动的人，通过面部识别附上他们的身份，并能够有效地执行禁止乱扔垃圾政策。通过减少对人工干预的依赖，降低人为错误，并提供及时的身份识别，所提出的系统在解决乱扔垃圾事件方面具有显著优势。本研究的最大贡献在于实施所提出的系统，利用先进技术增强监视操作并自动惩处乱扔垃圾者。
URL
https://arxiv.org/abs/2404.07467
