测绘学报 ›› 2022, Vol. 51 ›› Issue (3): 388-400.doi: 10.11947/j.AGCS.2022.20200507

• 地图学与地理信息 • 上一篇    下一篇

多视角监控视频中动态目标的时空信息提取方法

李景文1,2, 韦晶闪1, 姜建武1,2, 陆妍玲1, 刘垒2, 唐一飞3, 李旭2   

  1. 1. 桂林理工大学测绘地理信息学院, 广西 桂林 541004;
    2. 广西空间信息与测绘重点实验室, 广西 桂林 541004;
    3. 广西壮族自治区森林资源与生态环境监测中心, 广西 南宁 530000
  • 收稿日期:2020-10-30 修回日期:2021-11-20 发布日期:2022-03-30
  • 通讯作者: 姜建武 E-mail:fengbuxi@glut.edu.cn
  • 作者简介:李景文(1971-),男,博士生导师,研究方向为GIS理论和应用。E-mail:lijw@glut.edu.cn
  • 基金资助:
    国家自然科学基金(41961063);国家文化和旅游科技创新工程(2019-011);广西自然科学基金(2019GXNSFGA245001)

Spatio-temporal information extraction method for dynamic targets in multi-perspective surveillance video

LI Jingwen1,2, WEI Jingshan1, JIANG Jianwu1,2, LU Yanling1, LIU Lei2, TANG Yifei3, LI Xu2   

  1. 1. School of Surveying and Mapping and Geographic Information, Guilin University of Technology, Guilin 541004, China;
    2. Guangxi Key Laboratory of Spatial Information and Mapping, Guilin 541004, China;
    3. Guangxi Zhuang Autonomous Region Forest Resources and Ecological Environment Monitoring Center, Nanning 530000, China
  • Received:2020-10-30 Revised:2021-11-20 Published:2022-03-30
  • Supported by:
    The National Natural Science Foundation of China(No. 41961063);The National Culture and Tourism Science and Technology Innovation Project (No. 2019-011); Guangxi Natural Science Foundation of China (No. 2019GXNSFGA245001)

摘要: 监控视频中动态目标的精准定位与跟踪作为计算机视觉领域中重要的研究方向,近年来已成为监控领域的研究热点。传统视频动态目标检测仅依赖图像特征数据,忽略了与地理坐标系精准匹配,特别是对于多个摄像机覆盖的区域,拍摄的角度不同,投影后形成的图像空间分辨率也不同,因此,难以满足智能监控在复杂的地理场景中全方位时空信息感知。本文提出一种多摄像头协同的视频监控图像与地理空间数据互映射模型构建方法来获取动态目标的轮廓和地理位置等时空信息,首先建立监控图像信息与地理空间数据的互映射关系,将观测角度不同、尺度不同和空间分辨率的监控图像置于同一坐标系下,并在此基础上通过融合Canny算子与背景减法来检测目标的边缘信息;然后采用质心偏移算法还原目标在该场景的实际位置,从而实现多角度下连续跟踪,提升地理场景的时空理解力和分析力,提高动态目标的精准定位与跟踪能力。

关键词: 多视角, 动态目标检测, 特征信息提取, 地理空间映射

Abstract: As an important research direction in the field of computer vision, the precise positioning and tracking of dynamic targets in surveillance video has become a research hotspot in the surveillance field in recent years.Traditional video dynamic target detection relies only on image feature data, ignoring accurate matching with geographic coordinate systems.Especially for the area covered by multiple cameras, the spatial resolution of the image formed after projection is different when the shooting angle is different.Therefore, it is difficult to satisfy intelligent monitoring in complex geographical scenes with all-round spatio-temporal information perception.In this paper, we propose a collaborative video surveillance image and geospatial data inter-mapping model construction method to obtain spatio-temporal information such as the outline and geographic location of dynamic targets.Firstly, the mutual mapping relationship between surveillance image information and geospatial data is established, and the surveillance images with different observation angles, scales and spatial resolutions are placed under the same coordinate system.And based on this, the edge information of the target is detected by fusing Canny operator and background subtraction, and then the actual position of the target in the scene is restored by using the center-of-mass offset algorithm.This enables continuous tracking of targets under multiple angles, improves the spatio-temporal understanding and analysis of geographic scenes, and enhances the precise positioning and tracking of dynamic targets.

Key words: multi-view, dynamic target detection, feature information extraction, geospatial mapping

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