引用本文: | 王自然,张亚南,刘学军,等.视频传感器覆盖范围精细化计算方法[J].国防科技大学学报,2015,37(5):54-60.[点击复制] |
WANG Ziran,ZHANG Yanan,LIU Xuejun,et al.Fine camera coverage calculation method[J].Journal of National University of Defense Technology,2015,37(5):54-60[点击复制] |
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视频传感器覆盖范围精细化计算方法 |
王自然1, 张亚南2,3,4, 刘学军2,3,4, 王美珍2,3,4 |
(1. 南京师范大学泰州学院, 江苏 泰州 225300;2. 南京师范大学 地理科学学院, 江苏 南京 210023;3.
3. 江苏省地理信息资源开发与利用协同创新中心, 江苏 南京 210023;4.
4.警用地理信息技术公安部重点实验室, 江苏 常州 213022)
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摘要: |
视频传感器覆盖范围计算是视频传感器网络初始配置、优化部署等的核心基础,其精度严重影响覆盖分析的结果,然而现有很多方法并未考虑计算方法执行效率与精度的影响,而方法的精度与效率在大范围监控视频覆盖分析应用中显得尤为重要。因此,提出一种兼顾速度与精度的视频传感器覆盖范围计算方法,将地理空间进行格网化;计算每个格网角点被视频传感器覆盖的状况,用0或1表示;接着,以格网四个角点的覆盖情况描述格网的覆盖情况,将格网分为16种覆盖状态;逐步细化整个格网覆盖状态非(0000)和(1111)的格网,直至达到预设精度;获得视频传感器的覆盖范围。实验结果表明,该方法能够更为精确地获得部署在地理场景中视频传感器的覆盖范围,同时兼顾了计算方法的速度和精度。 |
关键词: 相机覆盖 覆盖分析 二值化网格 格网细化 |
DOI:10.11887/j.cn.201505009 |
投稿日期:2015-06-25 |
基金项目:国家自然科学基金资助项目(41401442,41201417);国家863计划资助项目(2015AA123901);江苏省高校自然科学研究面上资助项目(14KJB170011);博士学科点专项科研基金资助项目(新教师类)(20133207120017);江苏省测绘科研资助项目(JSCHKY201204);测绘遥感信息工程国家重点实验室资助项目(12E01);公安部科技强警基础工作专项资助项目(2014GABJC009);泰州市科技局科技支撑计划资助项目(TS036) |
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Fine camera coverage calculation method |
WANG Ziran1, ZHANG Yanan2,3,4, LIU Xuejun2,3,4, WANG Meizhen2,3,4 |
(1. Nanjing Normal University Taizhou College, Taizhou 225300, China;2. School of Geography Science, Nanjing Normal University, Nanjing 210023, China;3. Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China;4.
4. Key Laboratory of Police Geographic Information Technology Ministry of Public Security, Changzhou 213022, China)
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Abstract: |
Camera coverage is an important basis of camera network initial configuration, optimal deployment and so on. Its precision and efficiency are the critical influences on the results of coverage analysis, which are very important to the application of large area camera coverage analysis, but many methods do not consider them. A new method to efficiently estimate camera coverage was proposed. Firstly, the geographic space was dispersed into grids. Secondly, the statuses of the four corners of each grid were computed. If the corner was covered by the camera, the status was denoted by using 1 or 0. So the status of the gird can be presented by the code which is either 0 or 1. Consequently there are 16 statuses to represent the status of a grid. Finally, if the code of the grid was not (0000) or (1111), the gird would be divided into four isometrical sub-girds until the sub girds were small enough or their codes were (0000) or (1111). According to the levels and statues of all grids, the whole camera coverage was estimated. Experimental results show that the proposed method can obtain more precise camera and can give consideration to both efficiency and accuracy. |
Keywords: camera coverage coverage analysis bi-valued grid grid-fractionizing |
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