CN106919902B - 一种基于cnn的车辆识别和轨迹追踪方法 - Google Patents
一种基于cnn的车辆识别和轨迹追踪方法 Download PDFInfo
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- 238000007781 pre-processing Methods 0.000 claims description 3
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- 238000012706 support-vector machine Methods 0.000 description 4
- 238000012544 monitoring process Methods 0.000 description 3
- 238000013528 artificial neural network Methods 0.000 description 2
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- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/58—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads
- G06V20/584—Recognition of moving objects or obstacles, e.g. vehicles or pedestrians; Recognition of traffic objects, e.g. traffic signs, traffic lights or roads of vehicle lights or traffic lights
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- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
- G06V20/41—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items
- G06V20/42—Higher-level, semantic clustering, classification or understanding of video scenes, e.g. detection, labelling or Markovian modelling of sport events or news items of sport video content
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- G—PHYSICS
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Families Citing this family (9)
Publication number | Priority date | Publication date | Assignee | Title |
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CN107766821B (zh) * | 2017-10-23 | 2020-08-04 | 江苏鸿信系统集成有限公司 | 基于卡尔曼滤波与深度学习的视频中全时段车辆检测跟踪方法及系统 |
CN107886055A (zh) * | 2017-10-27 | 2018-04-06 | 中国科学院声学研究所 | 一种用于车辆运动方向判定的逆行检测方法 |
CN108198232B (zh) * | 2017-12-14 | 2021-04-16 | 浙江大华技术股份有限公司 | 一种轨迹框绘制的方法及设备 |
CN109376572B (zh) * | 2018-08-09 | 2022-05-03 | 同济大学 | 基于深度学习的交通视频中实时车辆检测与轨迹跟踪方法 |
CN109739234B (zh) * | 2019-01-02 | 2022-05-17 | 中电海康集团有限公司 | 一种基于gps轨迹数据的车辆实时图像追踪方法 |
CN109766841B (zh) * | 2019-01-10 | 2022-03-29 | 深圳大学 | 车辆检测方法、装置及计算机可读存储介质 |
CN109961061A (zh) * | 2019-04-15 | 2019-07-02 | 艾物智联(北京)科技有限公司 | 一种边缘计算视频数据结构化方法及系统 |
CN112911203B (zh) * | 2019-11-19 | 2022-04-26 | 杭州海康威视数字技术股份有限公司 | 获取目标轨迹的摄像机 |
CN116930956B (zh) * | 2023-09-19 | 2023-11-17 | 南京隼眼电子科技有限公司 | 基于目标尺寸的目标轨迹拼接方法、装置及存储介质 |
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CN105184271A (zh) * | 2015-09-18 | 2015-12-23 | 苏州派瑞雷尔智能科技有限公司 | 一种基于深度学习的车辆自动检测方法 |
CN106127802A (zh) * | 2016-06-16 | 2016-11-16 | 南京邮电大学盐城大数据研究院有限公司 | 一种运动目标轨迹追踪方法 |
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CN105184271A (zh) * | 2015-09-18 | 2015-12-23 | 苏州派瑞雷尔智能科技有限公司 | 一种基于深度学习的车辆自动检测方法 |
CN106127802A (zh) * | 2016-06-16 | 2016-11-16 | 南京邮电大学盐城大数据研究院有限公司 | 一种运动目标轨迹追踪方法 |
Non-Patent Citations (2)
Title |
---|
"一种改进的Sobel算子边缘检测及细化算法";沈德海,等;《渤海大学学报( 自然科学版)》;20140930;参见第2节 * |
"基于深度学习的图像目标定位识别研究";程欣;《万方数据知识服务平台》;20161102;第3.2.2、4.4节 * |
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Application publication date: 20170704 Assignee: Jiangsu Yanan Information Technology Co.,Ltd. Assignor: NUPT INSTITUTE OF BIG DATA RESEARCH AT YANCHENG Contract record no.: X2023980049133 Denomination of invention: A CNN based vehicle recognition and trajectory tracking method Granted publication date: 20210101 License type: Common License Record date: 20231203 Application publication date: 20170704 Assignee: Yancheng Nongfu Technology Co.,Ltd. Assignor: NUPT INSTITUTE OF BIG DATA RESEARCH AT YANCHENG Contract record no.: X2023980049126 Denomination of invention: A CNN based vehicle recognition and trajectory tracking method Granted publication date: 20210101 License type: Common License Record date: 20231203 Application publication date: 20170704 Assignee: Yanmi Technology (Yancheng) Co.,Ltd. Assignor: NUPT INSTITUTE OF BIG DATA RESEARCH AT YANCHENG Contract record no.: X2023980049119 Denomination of invention: A CNN based vehicle recognition and trajectory tracking method Granted publication date: 20210101 License type: Common License Record date: 20231203 |