首页> 外文期刊>Journal of Advanced Transportation >Computer vision approach for the classification of bike type (motorized versus non-motorized) during busy traffic in the city of Shanghai
【24h】

Computer vision approach for the classification of bike type (motorized versus non-motorized) during busy traffic in the city of Shanghai

机译:上海市繁忙交通中使用计算机视觉方法对自行车类型(电动和非电动)进行分类

获取原文
获取原文并翻译 | 示例
       

摘要

This article describes a novel approach for the binary classification of two-wheeler road users in a dense mixed traffic intersection. The classification is a supervised procedure to differentiate between motorized and non-motorized (human-powered) bikes. Road users were first detected and tracked using object recognition methods. Classification features were then selected from the collected trajectories. The features include maximum speed, cadence frequency in addition to acceleration-based parameters. Experiments were conducted on a video data set from Shanghai, China, where cyclists as well as motorcycles tend to share the main road facilities. A sensitivity analysis was performed to assess the quality of the selected features in improving the accuracy of the classification. A performance analysis demonstrated the robustness of the proposed classification method with a correct classification rate of up to 93%. This research contributes to the literature of automated data collection and can benefit the applications in many transportation-related fields such as shared space facility planning, simulation models for two-wheelers, and behavior analysis and road safety studies. Copyright (c) 2015 John Wiley & Sons, Ltd.
机译:本文介绍了一种在密集的混合交通路口对两轮道路用户进行二元分类的新颖方法。分类是一种监督程序,用于区分电动和非电动(人力)自行车。首先使用对象识别方法检测并跟踪道路使用者。然后从收集的轨迹中选择分类特征。这些功能包括最大速度,节奏频率以及基于加速度的参数。在来自中国上海的视频数据集上进行了实验,骑自行车的人和摩托车往往共享主要的道路设施。进行了敏感性分析,以评估所选特征的质量,以提高分类的准确性。性能分析证明了该分类方法的鲁棒性,正确分类率高达93%。这项研究为自动数据收集的文献做出了贡献,并且可以使许多运输相关领域的应用受益,例如共享空间设施规划,两轮车仿真模型以及行为分析和道路安全研究。版权所有(c)2015 John Wiley&Sons,Ltd.

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号