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    题名: Traffic Violation Detection via Depth and Gradient Angle Change
    作者: 彭彥璁
    Peng, Yan-Tsung;Liu, Chen-Yu;Liao, He-Hao;Lien, Wei-Cheng;Hsu, Gee-Sern Jison
    贡献者: 資訊系
    关键词: Traffic violation detection;intelligent transportation system;vehicle action analysis
    日期: 2022-11
    上传时间: 2024-02-16 15:36:57 (UTC+8)
    摘要: The paper aims to develop an effective traffic violation detection system to detect traffic violations automatically from videos reported by the public, especially for case footage recorded by dashcams facing forward mounted on vehicles or helmets. We aim to address two types of traffic violations: (1) running a red light and (2) turning on a red light. The proposed traffic violation detection system includes two main parts: Violation Target Tracking (VTT) and Target Action Analysis (TAA). First, we detect red traffic lights and vehicles and obtain their locations and depths in VTT. Next, we model the vehicles’ depth and gradient angle changes to catch traffic violations. The experimental results show that our violation detection system can achieve 76.1% true accuracy and 81.9% conditional accuracy on average for all the violation cases.
    關聯: IEEE 7th International Conference on Intelligent Transportation Engineering (ICITE), IEEE
    数据类型: conference
    DOI 連結: https://doi.org/10.1109/ICITE56321.2022.10101435
    DOI: 10.1109/ICITE56321.2022.10101435
    显示于类别:[資訊科學系] 會議論文

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