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Research and Design of Video Detection and Tracking Platform for Inland Waterway Vessel Based on Hadoop

机译:基于Hadoop的内河航道视频检测与跟踪平台的研究与设计

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Inland waterway vessel video has a very important role in the automated management of inland waterways. However, there is currently no open platform for implementing video processing of inland waterway vessels. According to the characteristics of large video and video formats of inland vessel, the paper proposes to build a standard video library for inland vessel and establish a video processing platform for inland vessels based on Hadoop, which adopts B/S architecture, with Html, CSS and JavaScript as front desk technology, JSP, Servlet and JavaBean as background processing technology, and realizes the function of online processing video. Compared with the traditional stand-alone mode, HDFS provides a parallel computing model, Map Reduce, and a distributed file system called Hadoop. It realizes the parallel processing of inland river vessel video processing, improves the speed of inland river vessel video tracking and detection, and shortens the running time of the algorithm.
机译:内河航道视频在内河航道的自动化管理中具有非常重要的作用。但是,目前尚没有用于实施内河航道船只视频处理的开放平台。针对内河舰船大型视频和视频格式的特点,提出建立标准的内河舰船视频库,建立基于Hadoop的B / S架构,Html,CSS的内河舰船视频处理平台。以JavaScript为前台技术,以JSP,Servlet和JavaBean为后台处理技术,实现了视频在线处理功能。与传统的独立模式相比,HDFS提供了并行计算模型Map Reduce和称为Hadoop的分布式文件系统。它实现了内河船只视频处理的并行处理,提高了内河船只视频的跟踪和检测速度,缩短了算法的运行时间。

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