用行车记录仪自动识别两轮车违规，生成电子罚单。
DashCop: Automated E-ticket Generation for Two-Wheeler Traffic Violations Using Dashcam Videos
- 通过分割与关联模块精准绑定骑手与摩托车
- 在复杂场景下实现骑手与车辆的稳定追踪
- 基于400段标注视频数据集，适合交通执法研究
两轮机动车在亚太地区广泛使用，但超员载人和不戴头盔等危险驾驶行为导致事故频发。本文提出端到端的自动化电子罚单生成系统DashCop，利用车载行车记录仪视频检测两轮车交通违规。主要贡献包括：（1）新颖的分割与跨关联（SAC）模块，准确关联骑手与摩托车；（2）针对骑手与摩托车共存场景优化的跨关联追踪算法；（3）RideSafe-400数据集，涵盖400段标注的行车记录视频，用于超员与头盔违规检测。系统在该数据集上经大量评估，显著提升违规识别性能。
原文摘要 · Abstract (English)
Motorized two-wheelers are a prevalent and economical means of transportation, particularly in the Asia-Pacific region. However, hazardous driving practices such as triple riding and non-compliance with helmet regulations contribute significantly to accident rates. Addressing these violations through automated enforcement mechanisms can enhance traffic safety. In this paper, we propose DashCop, an end-to-end system for automated E-ticket generation. The system processes vehicle-mounted dashcam videos to detect two-wheeler traffic violations. Our contributions include: (1) a novel Segmentation and Cross-Association (SAC) module to accurately associate riders with their motorcycles, (2) a robust cross-association-based tracking algorithm optimized for the simultaneous presence of riders and motorcycles, and (3) the RideSafe-400 dataset, a comprehensive annotated dashcam video dataset for triple riding and helmet rule violations. Our system demonstrates significant improvements in violation detection, validated through extensive evaluations on the RideSafe-400 dataset.
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