| 基于视频的城市快速路车辆异常行为检测 |
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| 引用本文： | 蔡英凤,张为公,王海.基于视频的城市快速路车辆异常行为检测[J].现代交通技术,2012,9(1):60-63. |
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| 作者姓名： | 蔡英凤 张为公 王海 |
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| 作者单位： | 东南大学仪器科学与工程学院,江苏南京210096／汽车电子与智能交通技术重点实验室,江苏苏州215123 |
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| 基金项目： | 基金项目：“十一五”国家科技支撑计划项目（项目编号：2009BAG13A04）;江苏省自然科学基金（项目编号：BK2010239）;江苏省交通科学研究资助项目（项目编号：08X09） |
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| 摘 要： | 文章提出虚拟传感器的概念,针对城市快速路视频监控系统,改革单一功能摄像机,使其成为具人工智能的新型视频传感器,完成道路车辆跟踪及异常行为检测。异常检测算法运用带有时间和空间信息的车辆轨迹对自组织神经网络进行训练,获得神经网络参数后利用概率模型对实时车辆轨迹进行异常提取。该文所提算法能在嵌入式DM642视频处理平台上有效运行,能够提取诸如超低(高)速行驶、违章停车、违规掉头等异常行为,具有低运算量及较好的鲁棒性。
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| 关 键 词： | 视频监控 智能摄像机 行为理解 自组织神经网络 |
Video Based Vehicle Abnormal Behavior Detection for Urban Expressway |
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| Cai Yingfeng,Zhang Weigong,Wang Hai.Video Based Vehicle Abnormal Behavior Detection for Urban Expressway[J].Modern Transportation Technology,2012,9(1):60-63. |
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| Authors: | Cai Yingfeng Zhang Weigong Wang Hai |
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| Institution: | 1.School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China; 2.Key laboratory of Automotive Electronics and Intelligent Transportation, Suzhou 215123, China) |
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| Abstract: | A novel conception of virtual sensor is propesed for video based urban expressway monitoring system. Compared with traditional cameras,the new intelligent video sensor can carry out vehicle tracking and abnormal behavior detection. Abnormal detection algorithm finishes abnormal trajectories detection by probability model after training of self-organizing neural network using spatiotemporal trajectories data. The proposed algorithms are effectively running on the embedded DM642 video processing platform and feasible for robust detection of extra low or high speeding vehicles,illegal parking and illegal turning with low computational cost. |
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| Keywords: | video surveillance intelligent camera behavior understanding self-organizing neural network |
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